Lecture6.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Lecture 6: Scientific Python Ecosystem\n",
    "## October 22, 2019\n",
    "## Tristan Glatard\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Today's objectives \n",
    "1. Create data models with `numpy`, consolidate our knowledge of `matplotlib` and `pip`.\n",
    "2. Load and query data the easy way with `pandas`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Data models\n",
    "\n",
    "In this class, a data model is a way to summarize a (large) dataset using a mathematical formulation or a program.\n",
    "\n",
    "For instance, a line might be a good data model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from numpy import array\n",
    "x = array([1, 2, 3, 4, 5])\n",
    "y = array([ 3.3, 4.7, 7.4, 9.1, 10.9])\n",
    "plt.plot(x, y, '+')\n",
    "plt.plot(x, 1+2*x)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Or a very bad one:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = array([1, 2, 3, 4, 5])\n",
    "y = array([ 1.1, 4.2, 8.8, 16.5, 24])\n",
    "plt.plot(x, y, '+')\n",
    "plt.plot(x, 1+2*x)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "In this particular case, a polynomial of degree 2 is a better fit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXQAAAD8CAYAAABn919SAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAHhRJREFUeJzt3Xl8FPX9x/HXJyEcAnIIInIYRajiUcSIB4hIRFEQUPEWQaVoWxSttUVr69XDtla8Wv2hWBGvcko4FBFRPNGAKEckIIIcAQLIfSb5/v6YtUVMyObY/e5O3s/HI49sZmeZtwP7dvLdme+Ycw4REUl+Kb4DiIhI5VChi4iEhApdRCQkVOgiIiGhQhcRCQkVuohISKjQRURCQoUuIhISKnQRkZCoFs+NNWrUyKWnp8dzkyIiSW/OnDkbnHONS1svroWenp5OdnZ2PDcpIpL0zGxFNOtpyEVEJCRU6CIiIaFCFxEJCRW6iEhIqNBFREKi1EI3sxZmNtPMFpnZQjMbEll+v5mtNrN5ka+LYh9XRERKEs1piwXAnc65uWZWF5hjZtMjzw1zzj0Su3giIhKtUo/QnXN5zrm5kcfbgBygWayDiYiEwt4d8MZvYdfmmG+qTGPoZpYOnALMjiwabGZfmtnzZtaghNcMMrNsM8vOz8+vUFgRkaSyZxu81Bc+HQ4rZ5e+fgVFXehmVgcYB9zunNsKPA20AtoBecA/inudc264cy7DOZfRuHGpV66KiITDrs0w6pKgyC8bAW0uiPkmoyp0M0sjKPOXnXPjAZxz65xzhc65IuBZoEPsYoqIJJGdm2BUH1gzD64YCSdeGpfNRnOWiwEjgBzn3KP7LW+632qXAAsqP56ISJLZsRFe7AXrFsKVL8HxF8dt09Gc5dIR6AfMN7N5kWX3AFebWTvAAcuBm2OSUEQkWWxfDyN7wXffwNWvwbGZcd18qYXunPsAsGKemlr5cUREktTWvODIfMsquGY0HHPOD54eNj2XO7q1iWkEXSkqIlJRW1bBCxfB1jVw3bgflTnA4zOWxDxGXOdDFxEJne9WwMiewVkt/SZAC3/nh6jQRUTKa+PXwZj53u1w/URo1v4HTw+bnvuDI/P0oVMAGJLZOibDL+acq/Q/tCQZGRlOdywSkVDIzw3GzAv3Qr/XoenJB109fegUlj/co1ybMrM5zrmM0tbTEbqISFmtWwQv9gYc9J8MTdr6TgToQ1ERkbJZOz8YM7cUGDA16jIfktk6xsFU6CIi0VvzObzQE6rVhBumQuPox8FjfcoiaMhFRCQ6Kz+Dly6DWvWg/yRokO470Y/oCF1EpDQrPg7mZjmkYTDMkoBlDip0EZGD+2YWvHQp1G0aDLPUb+E7UYlU6CIiJVk6A16+HOq3hAFT4NAjfSc6KBW6iEhxcqfBq1fBYa2DMq/bxHeiUqnQRUQOlDMZXrsWDm8L/bOgdiPfiaKiQhcR2d/CCTCmPxzZLric/5CGvhNFTYUuIvK9L0fD2Buh+Wlw3XioVd93ojJRoYuIAHz+EowfBEd1hGvHQs1DfScqMxW6iEj2v2HiL+GYLsHNKWrU8Z2oXFToIlK1zR4Ok2+H1hcEt42rfojvROWmQheRquujJ+GNu+C4nsENndNq+k5UIZrLRUSqplmPwDsPQds+cNlzkJrmO1GFqdBFpGpxDt59GN57GE66Avo8DanhqMJw/FeIiETDOZjxIHzwKLS7Fno9CSmpvlNVGhW6iFQNzsFb98LHT8GpN0CPRyElXB8jqtBFJPyKiuDN38Knw6HDzXDhX8HMd6pKp0IXkXArKgpOS5w7Es4cDOf/MZRlDip0EQmzokLIuhXmvQxn3wldfx/aMgcVuoiEVWEBvH4LzB8DXe6Bc34T6jIHFbqIhFHhPhg3EBa9Dpn3wdm/8p0oLlToIhIuBXtgzA2weAqc/yc4a7DvRHGjQheR8Ni3G0b3gyVvwYV/h9MH+U4UVyp0EQmHvTvhtWtg2bvQ8zHIuMF3orhToYtI8tuzPbj/5/IPoPc/4ZRrfSfyotTLpMyshZnNNLNFZrbQzIZEljc0s+lmtiTyvUHs44qIHGD3VnjpMljxEVz6bJUtc4hu+twC4E7nXFvgDOCXZtYWGArMcM61BmZEfhYRiZ9dm2HUJbA6G/qOgJMv953Iq1IL3TmX55ybG3m8DcgBmgG9gZGR1UYCfWIVUkTkR3Zughd7Qd4XcMWLcMIlvhN5V6aZacwsHTgFmA00cc7lRZ5aCzQp4TWDzCzbzLLz8/MrEFVEJGLHBhh5Maz/Cq56BY7r4TtRQoi60M2sDjAOuN05t3X/55xzDnDFvc45N9w5l+Gcy2jcuHGFwoqIsG0dvNADNn4N17wGbc73nShhRFXoZpZGUOYvO+fGRxavM7OmkeebAutjE1FEJGLrGnjhIti8Eq4dA626+k6UUKI5y8WAEUCOc+7R/Z7KAvpHHvcHJlZ+PBGRiM0r4d8XBUfo/cbD0Wf7TpRwojkPvSPQD5hvZvMiy+4BHgZGm9lNwArgithEFJEqb9M3MLIX7N4C178OzTN8J0pIpRa6c+4DoKQpyjIrN46IyAE2fh18ALpvJ/SfCEee4jtRwtKVoiKSuPIXB0fmRfug/yQ44iTfiRKaCl1EEtO6RcF55hgMmAKHH+87UcIL1x1SRSQc8r4ITk1MqQY3TFWZR0mFLiKJZfWcYMw87ZDgyLxRa9+JkoaGXEQkcaz8NJhoq1aDYMy8wVG+EyUVHaGLSGJY/mEw0VbtxsEwi8q8zFToIuLfsnfh5b5w6JFBmddr7jtRUlKhi4hfS9+GV66EBunBmHndI3wnSloqdBHxZ/Eb8OrVwQef/SdDncN9J0pqKnQR8WNRFvznOmhyAlyfBbUP850o6anQRST+FoyDMQPgyPZw/UQ4pKHvRKGgQheR+PriNRg3EFqcHsyaWLOe70ShoUIXkfiZOwom3ALpneC6sVCjru9EoaJCF5H4+Ow5yBoc3JTimtFQvbbvRKGjQheR2PvkaZhyJ7TpHtwDNK2W70ShpEIXkdj68HF4cygcfzFcMQrSavpOFFqay0VEYue9v8PMP8IJl8KlwyE1zXeiUFOhi0jlcw5m/hlm/Q1Ovgp6/xNSVTexpj0sIpXLOXj7fvjwMTjlOrj4CUhJ9Z2qSlChi0jlcQ6m3QOf/AsyboKLHoEUfVQXL9rTIlJmw6bn/nhhURFM/XVQ5qf/HHr8Q2UeZ9rbIlJmj89Y8sMFRUUweUhwrvlZt0H3v4CZn3BVmIZcRKRiigph4i/hi1eh811w7u9U5p6o0EUkKsOm5/7gyDx96BRSKWRK81Ect+GtoMjP+Y3HhGLOubhtLCMjw2VnZ8dteyISG+lDp7D8j91g3E2QkwXnPQCdbvcdK7TMbI5zLqO09XSELiJlVp19MPp6yH0DLvgLnPkL35EEFbqIlNXenUw74hnI/Tg4LbHDz3wnkggVuohELz8XxvTn6M05wQVDp/b3nUj2o0IXkeh8OQYmDQkm17puLBx7nu9EcgAVuogc3L7dMO1uyH4eWpwBfZ+Hes18p5JiqNBFpGSblsHo/rD2S+g4BLr+XjMmJjAVuogUb1FWcMGQGVz1Khx3ke9EUopSL/03s+fNbL2ZLdhv2f1mttrM5kW+9DctEhYFe+HNu2F0PzjsWLj5fZV5kojmCP0F4CngxQOWD3POPVLpiUTEn80rYcwAWJ0NHW6G8x+CajV8p5IolVrozrlZZpYe+ygi4lXuNJhwMxQWwOUvwAmX+E4kZVSR2RYHm9mXkSGZBpWWSETiq7AguCHFK1fAoc3h5vdU5kmqvIX+NNAKaAfkAf8oaUUzG2Rm2WaWnZ+fX87NiUhMbM2DF3vBB8Pg1AEwcDoc1sp3Kimncp3l4pxb9/1jM3sWmHyQdYcDwyGYnKs82xORGPh6JowbCPt2wiXD4adX+k4kFVSuI3Qza7rfj5cAC0paV0QSTFEhvPswjLoEajeCn81UmYdEqUfoZvYq0AVoZGargPuALmbWDnDAcuDmGGYUkcqyPR/GD4Rl78LJV0HPR6F6bd+ppJJEc5bL1cUsHhGDLCISS8s/hLE3wu7NwcRa7a/XnYVCRleKioRdURF89DjMeAgapAcTax1xku9UEgMqdJEw27kJJtwCS6ZB2z7Q60moeajvVBIjKnSRsFqVHVz1uW1tcCOK0wZqiCXkVOgiYeMczH4G3vo9HNoUbpoGzU71nUriQIUuEia7twQzJOZMgjYXwiVPQy1dyF1VqNBFwmLNPBjTP5hg6/w/wpmDNcRSxajQRZKdc8HdhN68Gw45DG6YCi3P8J1KPFChiySzPdth8u0wfwy0yoRLhwdXf0qVpEIXSVbrFgVDLBuXQtd7odOdkFKRCVQl2anQRZLRvFdg8q+gRl24fiIc3dl3IkkAKnSRZLJ3J7xxF3z+EqSfDZeNgLpNfKeSBKFCF0kWG5bA6P6wfiF0vgvOGQqpegvL/+hfg0gymD8WJg2B1Opw7ThofZ7vRJKAVOgiiWzfbph2D2SPgBanQ9/noV5z36kkQanQRRLVpm+Cs1jyvoCzboXM+yA1zXcqSWAqdJFElDMZXv8FGHDVK3BcD9+JJAmo0EUSSeE+ePt++PgpOPIUuPyFYA5zkSio0EUSxeaVMPYGWPUZdBgUzMdSrYbvVJJEVOgiiSD3LZgwCAoLoO+/4cRLfSeSJKRCF/GpsABm/gk+eBSanAiXj4RGx/pOJUlKhS7iy9Y8GHcTrPgwuGHzhX+DtFq+U0kSU6GL+LDsXRg3EPbugD7PQLurfSeSEFChi8RTUSHMegTe/Qs0agP9J8Hhx/tOJSGhQheJl+35MP5nsGwmnHQF9BwGNer4TiUhokIXiYcVH8HYG2HnJrj4cWjfX7eHk0qnQheJpaIi+OgJmPEgNDgKBr4NTU/2nUpCSoUuEis7N8HrP4fcN6Ftb+j1JNSs5zuVhJgKXSQWVs0JJtbatjY4HbHDIA2xSMyp0EUqk3Mw+//grXuhblO4cRo0P9V3KqkiVOgilWX3Fpg4GHKyoE136PM0HNLQdyqpQlToIpUh74vg9nCbv4VuD8KZt0JKiu9UUsWo0EUqwjmY8wK88dvgaHzAFDjqTN+ppIoq9RDCzJ43s/VmtmC/ZQ3NbLqZLYl8bxDbmCIJaM92GD8IJt8O6R3hlg9U5uJVNL8TvgB0P2DZUGCGc641MCPys0jVsT4Hnj0XFoyFc38H146F2o18p5IqrtRCd87NAjYdsLg3MDLyeCTQp5JziSSuea/C8HNh12bo9zqc8xtISfWdSqTcY+hNnHN5kcdrgSaVlEckce3bBVPvgs9HwVGdoO8IqHuE71Qi/1XhD0Wdc87MXEnPm9kgYBBAy5YtK7o5ET82LA0uFFq3AM6+E7rcA6k6p0ASS3nPq1pnZk0BIt/Xl7Sic264cy7DOZfRuHHjcm5OxKMF42D4ObB1dTBWnvkHlbkkpPIWehbQP/K4PzCxcuKIJJCCPTDl18EsiYe3Dc5iad3NdyqREpV6mGFmrwJdgEZmtgq4D3gYGG1mNwErgCtiGVIk7r5bHlwolDcPzhwM590PqWmeQ4kcXKmF7pwr6d5YmZWcRSQxfDUFJvw8eHzly3B8T795RKKkgUCR7xXug7fvh4+fgqbt4PIXoOHRvlOJRE2FLgKwZRWMuQFWfQqnDYQL/gzVavhOJVImKnSp2ooK4cv/sGvyUGqlFMJlI+Ckvr5TiZSLCl2qJudgyfRgiGX9QhYXHUO720ZDo9a+k4mUmwpdqp5Vc+Dt+2D5+9DgaOj7b/q8VJ3lKnNJcip0qTo2fh3crHnR63BII9455i5uXnQS+14K3gbpQ6cAMCSzNXd0a+MzqUi5qNAl/Lavh/f+GsxbnloDzhkKZw2ma426LImskj50Cssf7uEzpUiFqdAlvPZsg4+ego+ehMI9cOoA6PwbqKu55CScVOgSPoX7gqPx9/4KO/KhbZ9g/pXDWpX4kiGZGj+X5KdCl/BwDhZOgHcegk3Lgilur/4PND+11JdqzFzCQIUu4fDNLJh+H6yZG0ykdc2YYCItM9/JROJGhS7Jbe2C4FzypdPh0ObQ52k4+UrdQUiqJBW6JKfNK2Hmn+CL16BmPej2EHQYBGk1fScT8UaFLsll5yZ4/x/w6bPBzx1vg053QK0GfnOJJAAVuiSHfbtg9jPw/jDYsxXaXQvn3g31mvtOJpIwVOiS2IoKYd4rMPPPsG0NtOkOmfdBk7a+k4kkHBW6JCbnIPdNePsByM+BZhlw2bOQ3sl3MpGEpUKXxLPyM5j+B/j2I2jYCq54EY7vpVMQRUqhQpfEsWEJzHgAciZB7cOhx6PQ/nrdy1MkSip08W/bWnj3YZj7IqTVgnN/B2f8AmrU8Z1MJKmo0MWf3Vvhoyfg439C4d7g1m+d74I6jX0nE0lKKnSJv4K9kP08zPob7NwIJ1wKmb+Hhsf4TiaS1FToEj9FRbBwfDB51nfL4ejOcN4D0Ky972QioaBCl/hY9m4weVbePGhyElw3Dlpl6swVkUqkQpfYyvsyuH/n1+9AvZZwyXA46XJISfGdTCR0VOgSG9+tgHf+CPNHB/OsXPBnyLhJk2eJxJAKXSrXjo3w/iPw2XNgKcHEWR1vh1r1fScTCT0VulSOvTth9tPwwWOwd3tk8qx74NAjfScTqTJU6FIxhQUw72V49y+wLQ9+clEwedbhx/lOJlLlqNClfJyDxVODybM2LIbmHaDvv+GoM30nE6myVOhSdt9+EpyCuPITOKw1XPkyHNdDpyCKeKZCl+jlLw6OyBdPgTpHQM/H4JR+kKp/RiKJoELvRDNbDmwDCoEC51xGZYSSBLM1Lxgj/3wUpNWGrvcGk2dVr+07mYjspzIOrc51zm2ohD9HEs3uLfDh4/Dxv6CoADrcHEyeVfsw38lEpBj6XVl+rGAPfDYCZv0ddm0Kruzsei80SPedTEQOoqKF7oC3zMwB/+ecG14JmcSXoiJYMDaYPGvzt3DMudDtAWj6U9/JRCQKFS30Ts651WZ2ODDdzL5yzs3afwUzGwQMAmjZsmUFNycxs3RGMOfK2vlwxMnQ73Fo1dV3KhEpgwoVunNudeT7ejObAHQAZh2wznBgOEBGRoaryPYkBtZ8Dm/fH8yGWL8lXPocnHiZJs8SSULlLnQzqw2kOOe2RR6fDzxYackktjZ9EwytLBgHtRpC94ch40aoVsN3MhEpp4ocoTcBJlhwMUk14BXn3JuVkkpiZ8cGeO9vwR2DUqrB2b+GjrdBzXq+k4lIBZW70J1zywB9Wpaghk3P5Y5ubf63YO+O4N6dHz4B+3ZC+35wzlA4tKm/kCJSqXTaYkg9PmNJUOiF+2Dui/DeX2H7OjiuZzB5VuM2pf8hIpJUVOih5WDRRJjxIGxcCi3OgCtGQcvTfQcTkRhRoYfIsOm5PDtjPl1TPmd89Tdg9FKWFDVjUdtH6H3lQE2eJRJyKvQw2LUZct/kjg0TuaP2DCjcwxrXEHo9SeufXkNrTZ4lUiXonZ6sdmyAr6ZAThYsew+K9kHdIyHjBji+F52e2cSy9hf7TikicaRCTyZb8+CrycHY+IoPwRVB/aPgjFvg+N7Q7NT/XhB0a2au57AiEm8q9ES3+VvImQSLsmDlbMBBozbQ6VfQtldwmX4xY+M/OGVRRKoEFXoi2vh1cBSekxVcmg/Q5ETocje07a37dYpIsVToicA5yP8qKPFFWbB+YbD8yPZw3v1wfC84rJXPhCKSBFTovjgHeV8ER+GLsmDjEsCg5RlwwV/g+IuhfgvfKUUkiajQ46moCFbPgUWvB+Pim1eApUB6Jzj95qDE6x7hO6WIJCkVeqwVFcK3HwdH4TmTYNsaSEmDY7pA51/DT3rolm4iUilU6LFQuA++mRUMp3w1BXbkQ7Wa0CoT2t4HbbpDrfq+U4pIyKjQK8u+3bBsZnAkvngq7N4MabWhzfnBh5qtz4cadXynFJEQU6FXxN4dsPTtoMRzp8HebVCjHvyke3B6YauukFbLd0oRqSJU6GW1e2tQ3jkTYcnbULAruOPPCX2CEj/6HKhW3XdKEamCVOjR2LkJFr8RjIl//Q4U7oU6TeCUa4PhlKM6gibAEhHP1EIl2b4+Mm9KFix/H4oKoF4LOG1gUOItTteNlEUkoajQ97dldXBqYU5WcKqhK4KGx8CZg4N5U45srznFRSRhqdC/Wx45RzwLVn0WLGt8XHDz5La9ockJKnERSQpVs9Dzc4MPNRdlwdovg2VHnAxd7w2modX9NkUkCVWNQncO1i2MzJsyMZgIC6D5adDtoeCS+4ZH+80oIlJB4S1052DN3P8Np2xaBhgcdRZ0/2tQ4vWa+U4pIlJpwlXoRUWw6tPIXOKTYMtKsFQ4ujOcdSsc1xPqHO47pYhITCRNoQ+bnlv8XXgKC4LbseVkQc5k2L4WUqvDMecGN4T4yYVwSMP4BxYRibOkKfTHZyz5X6EX7IVv3guOxBdPhZ0boVotaH1e8KFmmwug5qF+A4uIxFnSFHoN9gYzFy6aCIvfhD1boHrdoLzb9oJjz4PqtX3HFBHxJqELfdj0XB6fsYRbU8czt8YkeG0Pm11tVjfpwgmZ/YJhlbSavmOKiCSEhC70O7q1CYZZPv+OV8Zt4poBg6l/dGfqp6b5jiYiknCSYzKSU67jnoKBcGwmqMxFRIqVHIUODMls7TuCiEhCS5pCL/aURRER+a8KFbqZdTezxWa21MyGVlYoEREpu3IXupmlAv8ELgTaAlebWdvKCiYiImVTkSP0DsBS59wy59xe4DWgd+XEEhGRsqpIoTcDVu7386rIMhER8SDmH4qa2SAzyzaz7Pz8/FhvTkSkyqpIoa8GWuz3c/PIsh9wzg13zmU45zIaN25cgc2JiMjBmHOufC80qwbkApkERf4ZcI1zbuFBXpMPrCjXBqERsKGcr40l5Sob5Sob5SqbRM0FFct2lHOu1CPicl/675wrMLPBwDQgFXj+YGUeeU25D9HNLNs5l1He18eKcpWNcpWNcpVNouaC+GSr0FwuzrmpwNRKyiIiIhWQNFeKiojIwSVToQ/3HaAEylU2ylU2ylU2iZoL4pCt3B+KiohIYkmmI3QRETmIhCp0M3vezNab2YISnjczeyIyGdiXZtY+QXJ1MbMtZjYv8vWHOOVqYWYzzWyRmS00syHFrBP3fRZlrrjvMzOraWafmtkXkVwPFLNODTP7T2R/zTaz9ATJNcDM8vfbXwNjnWu/baea2edmNrmY5+K+v6LM5WV/mdlyM5sf2WZ2Mc/H9v3onEuYL6Az0B5YUMLzFwFvAAacAcxOkFxdgMke9ldToH3kcV2C6wLa+t5nUeaK+z6L7IM6kcdpwGzgjAPW+QXwTOTxVcB/EiTXAOCpeP8bi2z7V8Arxf19+dhfUebysr+A5UCjgzwf0/djQh2hO+dmAZsOskpv4EUX+ASob2ZNEyCXF865POfc3MjjbUAOP55PJ+77LMpccRfZB9sjP6ZFvg78EKk3MDLyeCyQaWaWALm8MLPmQA/guRJWifv+ijJXoorp+zGhCj0KiTwh2JmRX5nfMLMT4r3xyK+6pxAc3e3P6z47SC7wsM8iv6bPA9YD051zJe4v51wBsAU4LAFyAVwW+TV9rJm1KOb5WHgM+A1QVMLzXvZXFLnAz/5ywFtmNsfMBhXzfEzfj8lW6IlqLsGluT8FngRej+fGzawOMA643Tm3NZ7bPphScnnZZ865QudcO4K5hzqY2Ynx2G5posg1CUh3zp0MTOd/R8UxY2Y9gfXOuTmx3lZZRJkr7vsropNzrj3BfSJ+aWad47RdIPkKPaoJweLNObf1+1+ZXXD1bJqZNYrHts0sjaA0X3bOjS9mFS/7rLRcPvdZZJubgZlA9wOe+u/+smC+onrARt+5nHMbnXN7Ij8+B5wahzgdgV5mtpzgfgddzeylA9bxsb9KzeVpf+GcWx35vh6YQHDfiP3F9P2YbIWeBVwf+aT4DGCLcy7PdygzO+L7cUMz60CwX2NeApFtjgBynHOPlrBa3PdZNLl87DMza2xm9SOPawHdgK8OWC0L6B953Bd4x0U+zfKZ64Bx1l4En0vElHPubudcc+dcOsEHnu845647YLW4769ocvnYX2ZW28zqfv8YOB848My4mL4fKzSXS2Uzs1cJzn5oZGargPsIPiDCOfcMwbwxFwFLgZ3ADQmSqy/wczMrAHYBV8X6H3VER6AfMD8y/gpwD9Byv2w+9lk0uXzss6bASAtun5gCjHbOTTazB4Fs51wWwf+IRpnZUoIPwq+KcaZoc91mZr2AgkiuAXHIVawE2F/R5PKxv5oAEyLHKdWAV5xzb5rZLRCf96OuFBURCYlkG3IREZESqNBFREJChS4iEhIqdBGRkFChi4iEhApdRCQkVOgiIiGhQhcRCYn/B6oo1ocfcv2TAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = array([1, 2, 3, 4, 5])\n",
    "y = array([ 1.1, 4.2, 8.8, 16.5, 24])\n",
    "plt.plot(x, y, '+')\n",
    "plt.plot(x, x**2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Numpy's `polyfit` function can find the \"best\" polynomial fit for a dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from numpy import polyfit, polyval\n",
    "\n",
    "# This finds the best polynomial that passes through x and y\n",
    "polynomial = polyfit(x, y, 2)\n",
    "\n",
    "plt.plot(x, y, '+')\n",
    "# Polyval evaluates the polynomial, i.e., computes y such as y = P(x)\n",
    "plt.plot(x, polyval(polynomial, x), '-')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Activity 1: polynomial models with numpy\n",
    "\n",
    "<img src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Antu_task-complete.svg/1024px-Antu_task-complete.svg.png\" width=50 align=left/>\n",
    "\n",
    "* Using `numpy`, import one patient of the arthritis dataset used in the previous lectures\n",
    "* Fit a line to this patient's data: does a line properly describe the number of inflammations for this patient?\n",
    "* Increase the degree of the polynomial model until you are satisfied with the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "import numpy\n",
    "a = numpy.loadtxt(fname='../arthritis/data/inflammation-01.csv', delimiter=',')\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "patient = a[7]\n",
    "plt.plot(patient)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy import arange\n",
    "x = arange(len(patient))\n",
    "line = polyfit(x, patient, 1)\n",
    "plt.plot(patient)\n",
    "plt.plot(x, polyval(line, x))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from numpy import arange\n",
    "poly = polyfit(x, patient, 3)\n",
    "plt.plot(patient)\n",
    "plt.plot(x, polyval(poly, x))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Loading data with pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Pandas is a major data manipulation library in Python. To begin, let's install it using `pip`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in /home/glatard/venvs/spark/lib/python3.7/site-packages (0.24.2)\n",
      "Requirement already satisfied: python-dateutil>=2.5.0 in /home/glatard/venvs/spark/lib/python3.7/site-packages (from pandas) (2.8.0)\n",
      "Requirement already satisfied: numpy>=1.12.0 in /home/glatard/venvs/spark/lib/python3.7/site-packages (from pandas) (1.16.1)\n",
      "Requirement already satisfied: pytz>=2011k in /home/glatard/venvs/spark/lib/python3.7/site-packages (from pandas) (2019.1)\n",
      "Requirement already satisfied: six>=1.5 in /home/glatard/venvs/spark/lib/python3.7/site-packages (from python-dateutil>=2.5.0->pandas) (1.12.0)\n",
      "\u001b[33mYou are using pip version 19.0.3, however version 19.3.1 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "There are 2 important data types in Pandas:\n",
    "    1. `Series`, describing 1D data\n",
    "    2. `DataFrame`, describing 2D data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "`Series` are similar to lists:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0     1\n",
      "1     3\n",
      "2     5\n",
      "3    10\n",
      "4     6\n",
      "5     8\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "s = pd.Series([1, 3, 5, 10, 6, 8])\n",
    "print(s)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "While `DataFrames` are similar to tables:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     A  B      C\n",
      "0  1.0  0   zero\n",
      "1  1.0  1    one\n",
      "2  1.0  2    two\n",
      "3  1.0  3  three\n"
     ]
    }
   ],
   "source": [
    "d = pd.DataFrame({'A': 1.,\n",
    "                  'B': arange(4),\n",
    "                  'C': [\"zero\", \"one\", \"two\", \"three\"]\n",
    "                 })\n",
    "print(d)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "DataFrames are very useful to load tabular data, such as our AirBnb dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>host_id</th>\n",
       "      <th>host_name</th>\n",
       "      <th>neighbourhood_group</th>\n",
       "      <th>neighbourhood</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>room_type</th>\n",
       "      <th>price</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>last_review</th>\n",
       "      <th>reviews_per_month</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>availability_365</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2539</td>\n",
       "      <td>Clean &amp; quiet apt home by the park</td>\n",
       "      <td>2787</td>\n",
       "      <td>John</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Kensington</td>\n",
       "      <td>40.64749</td>\n",
       "      <td>-73.97237</td>\n",
       "      <td>Private room</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>0.21</td>\n",
       "      <td>6</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2595</td>\n",
       "      <td>Skylit Midtown Castle</td>\n",
       "      <td>2845</td>\n",
       "      <td>Jennifer</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Midtown</td>\n",
       "      <td>40.75362</td>\n",
       "      <td>-73.98377</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>225</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>2019-05-21</td>\n",
       "      <td>0.38</td>\n",
       "      <td>2</td>\n",
       "      <td>355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3647</td>\n",
       "      <td>THE VILLAGE OF HARLEM....NEW YORK !</td>\n",
       "      <td>4632</td>\n",
       "      <td>Elisabeth</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.80902</td>\n",
       "      <td>-73.94190</td>\n",
       "      <td>Private room</td>\n",
       "      <td>150</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3831</td>\n",
       "      <td>Cozy Entire Floor of Brownstone</td>\n",
       "      <td>4869</td>\n",
       "      <td>LisaRoxanne</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Clinton Hill</td>\n",
       "      <td>40.68514</td>\n",
       "      <td>-73.95976</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>89</td>\n",
       "      <td>1</td>\n",
       "      <td>270</td>\n",
       "      <td>2019-07-05</td>\n",
       "      <td>4.64</td>\n",
       "      <td>1</td>\n",
       "      <td>194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5022</td>\n",
       "      <td>Entire Apt: Spacious Studio/Loft by central park</td>\n",
       "      <td>7192</td>\n",
       "      <td>Laura</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.79851</td>\n",
       "      <td>-73.94399</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>80</td>\n",
       "      <td>10</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-11-19</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5099</td>\n",
       "      <td>Large Cozy 1 BR Apartment In Midtown East</td>\n",
       "      <td>7322</td>\n",
       "      <td>Chris</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Murray Hill</td>\n",
       "      <td>40.74767</td>\n",
       "      <td>-73.97500</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>200</td>\n",
       "      <td>3</td>\n",
       "      <td>74</td>\n",
       "      <td>2019-06-22</td>\n",
       "      <td>0.59</td>\n",
       "      <td>1</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5121</td>\n",
       "      <td>BlissArtsSpace!</td>\n",
       "      <td>7356</td>\n",
       "      <td>Garon</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bedford-Stuyvesant</td>\n",
       "      <td>40.68688</td>\n",
       "      <td>-73.95596</td>\n",
       "      <td>Private room</td>\n",
       "      <td>60</td>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>2017-10-05</td>\n",
       "      <td>0.40</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>5178</td>\n",
       "      <td>Large Furnished Room Near B'way</td>\n",
       "      <td>8967</td>\n",
       "      <td>Shunichi</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hell's Kitchen</td>\n",
       "      <td>40.76489</td>\n",
       "      <td>-73.98493</td>\n",
       "      <td>Private room</td>\n",
       "      <td>79</td>\n",
       "      <td>2</td>\n",
       "      <td>430</td>\n",
       "      <td>2019-06-24</td>\n",
       "      <td>3.47</td>\n",
       "      <td>1</td>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5203</td>\n",
       "      <td>Cozy Clean Guest Room - Family Apt</td>\n",
       "      <td>7490</td>\n",
       "      <td>MaryEllen</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>40.80178</td>\n",
       "      <td>-73.96723</td>\n",
       "      <td>Private room</td>\n",
       "      <td>79</td>\n",
       "      <td>2</td>\n",
       "      <td>118</td>\n",
       "      <td>2017-07-21</td>\n",
       "      <td>0.99</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>5238</td>\n",
       "      <td>Cute &amp; Cozy Lower East Side 1 bdrm</td>\n",
       "      <td>7549</td>\n",
       "      <td>Ben</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Chinatown</td>\n",
       "      <td>40.71344</td>\n",
       "      <td>-73.99037</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>150</td>\n",
       "      <td>1</td>\n",
       "      <td>160</td>\n",
       "      <td>2019-06-09</td>\n",
       "      <td>1.33</td>\n",
       "      <td>4</td>\n",
       "      <td>188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5295</td>\n",
       "      <td>Beautiful 1br on Upper West Side</td>\n",
       "      <td>7702</td>\n",
       "      <td>Lena</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>40.80316</td>\n",
       "      <td>-73.96545</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>135</td>\n",
       "      <td>5</td>\n",
       "      <td>53</td>\n",
       "      <td>2019-06-22</td>\n",
       "      <td>0.43</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5441</td>\n",
       "      <td>Central Manhattan/near Broadway</td>\n",
       "      <td>7989</td>\n",
       "      <td>Kate</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hell's Kitchen</td>\n",
       "      <td>40.76076</td>\n",
       "      <td>-73.98867</td>\n",
       "      <td>Private room</td>\n",
       "      <td>85</td>\n",
       "      <td>2</td>\n",
       "      <td>188</td>\n",
       "      <td>2019-06-23</td>\n",
       "      <td>1.50</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5803</td>\n",
       "      <td>Lovely Room 1, Garden, Best Area, Legal rental</td>\n",
       "      <td>9744</td>\n",
       "      <td>Laurie</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>South Slope</td>\n",
       "      <td>40.66829</td>\n",
       "      <td>-73.98779</td>\n",
       "      <td>Private room</td>\n",
       "      <td>89</td>\n",
       "      <td>4</td>\n",
       "      <td>167</td>\n",
       "      <td>2019-06-24</td>\n",
       "      <td>1.34</td>\n",
       "      <td>3</td>\n",
       "      <td>314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>6021</td>\n",
       "      <td>Wonderful Guest Bedroom in Manhattan for SINGLES</td>\n",
       "      <td>11528</td>\n",
       "      <td>Claudio</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>40.79826</td>\n",
       "      <td>-73.96113</td>\n",
       "      <td>Private room</td>\n",
       "      <td>85</td>\n",
       "      <td>2</td>\n",
       "      <td>113</td>\n",
       "      <td>2019-07-05</td>\n",
       "      <td>0.91</td>\n",
       "      <td>1</td>\n",
       "      <td>333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>6090</td>\n",
       "      <td>West Village Nest - Superhost</td>\n",
       "      <td>11975</td>\n",
       "      <td>Alina</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>West Village</td>\n",
       "      <td>40.73530</td>\n",
       "      <td>-74.00525</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>90</td>\n",
       "      <td>27</td>\n",
       "      <td>2018-10-31</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>6848</td>\n",
       "      <td>Only 2 stops to Manhattan studio</td>\n",
       "      <td>15991</td>\n",
       "      <td>Allen &amp; Irina</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.70837</td>\n",
       "      <td>-73.95352</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>140</td>\n",
       "      <td>2</td>\n",
       "      <td>148</td>\n",
       "      <td>2019-06-29</td>\n",
       "      <td>1.20</td>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>7097</td>\n",
       "      <td>Perfect for Your Parents + Garden</td>\n",
       "      <td>17571</td>\n",
       "      <td>Jane</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Fort Greene</td>\n",
       "      <td>40.69169</td>\n",
       "      <td>-73.97185</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>215</td>\n",
       "      <td>2</td>\n",
       "      <td>198</td>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>1.72</td>\n",
       "      <td>1</td>\n",
       "      <td>321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>7322</td>\n",
       "      <td>Chelsea Perfect</td>\n",
       "      <td>18946</td>\n",
       "      <td>Doti</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>40.74192</td>\n",
       "      <td>-73.99501</td>\n",
       "      <td>Private room</td>\n",
       "      <td>140</td>\n",
       "      <td>1</td>\n",
       "      <td>260</td>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>2.12</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>7726</td>\n",
       "      <td>Hip Historic Brownstone Apartment with Backyard</td>\n",
       "      <td>20950</td>\n",
       "      <td>Adam And Charity</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Crown Heights</td>\n",
       "      <td>40.67592</td>\n",
       "      <td>-73.94694</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>99</td>\n",
       "      <td>3</td>\n",
       "      <td>53</td>\n",
       "      <td>2019-06-22</td>\n",
       "      <td>4.44</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>7750</td>\n",
       "      <td>Huge 2 BR Upper East  Cental Park</td>\n",
       "      <td>17985</td>\n",
       "      <td>Sing</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.79685</td>\n",
       "      <td>-73.94872</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>190</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>7801</td>\n",
       "      <td>Sweet and Spacious Brooklyn Loft</td>\n",
       "      <td>21207</td>\n",
       "      <td>Chaya</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71842</td>\n",
       "      <td>-73.95718</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>299</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "      <td>2011-12-28</td>\n",
       "      <td>0.07</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>8024</td>\n",
       "      <td>CBG CtyBGd HelpsHaiti rm#1:1-4</td>\n",
       "      <td>22486</td>\n",
       "      <td>Lisel</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Park Slope</td>\n",
       "      <td>40.68069</td>\n",
       "      <td>-73.97706</td>\n",
       "      <td>Private room</td>\n",
       "      <td>130</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>1.09</td>\n",
       "      <td>6</td>\n",
       "      <td>347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>8025</td>\n",
       "      <td>CBG Helps Haiti Room#2.5</td>\n",
       "      <td>22486</td>\n",
       "      <td>Lisel</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Park Slope</td>\n",
       "      <td>40.67989</td>\n",
       "      <td>-73.97798</td>\n",
       "      <td>Private room</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>0.37</td>\n",
       "      <td>6</td>\n",
       "      <td>364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>8110</td>\n",
       "      <td>CBG Helps Haiti Rm #2</td>\n",
       "      <td>22486</td>\n",
       "      <td>Lisel</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Park Slope</td>\n",
       "      <td>40.68001</td>\n",
       "      <td>-73.97865</td>\n",
       "      <td>Private room</td>\n",
       "      <td>110</td>\n",
       "      <td>2</td>\n",
       "      <td>71</td>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>0.61</td>\n",
       "      <td>6</td>\n",
       "      <td>304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>8490</td>\n",
       "      <td>MAISON DES SIRENES1,bohemian apartment</td>\n",
       "      <td>25183</td>\n",
       "      <td>Nathalie</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bedford-Stuyvesant</td>\n",
       "      <td>40.68371</td>\n",
       "      <td>-73.94028</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>2</td>\n",
       "      <td>88</td>\n",
       "      <td>2019-06-19</td>\n",
       "      <td>0.73</td>\n",
       "      <td>2</td>\n",
       "      <td>233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>8505</td>\n",
       "      <td>Sunny Bedroom Across Prospect Park</td>\n",
       "      <td>25326</td>\n",
       "      <td>Gregory</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Windsor Terrace</td>\n",
       "      <td>40.65599</td>\n",
       "      <td>-73.97519</td>\n",
       "      <td>Private room</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>2019-06-23</td>\n",
       "      <td>1.37</td>\n",
       "      <td>2</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>8700</td>\n",
       "      <td>Magnifique Suite au N de Manhattan - vue Cloitres</td>\n",
       "      <td>26394</td>\n",
       "      <td>Claude &amp; Sophie</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Inwood</td>\n",
       "      <td>40.86754</td>\n",
       "      <td>-73.92639</td>\n",
       "      <td>Private room</td>\n",
       "      <td>80</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>9357</td>\n",
       "      <td>Midtown Pied-a-terre</td>\n",
       "      <td>30193</td>\n",
       "      <td>Tommi</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hell's Kitchen</td>\n",
       "      <td>40.76715</td>\n",
       "      <td>-73.98533</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>150</td>\n",
       "      <td>10</td>\n",
       "      <td>58</td>\n",
       "      <td>2017-08-13</td>\n",
       "      <td>0.49</td>\n",
       "      <td>1</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>9518</td>\n",
       "      <td>SPACIOUS, LOVELY FURNISHED MANHATTAN BEDROOM</td>\n",
       "      <td>31374</td>\n",
       "      <td>Shon</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Inwood</td>\n",
       "      <td>40.86482</td>\n",
       "      <td>-73.92106</td>\n",
       "      <td>Private room</td>\n",
       "      <td>44</td>\n",
       "      <td>3</td>\n",
       "      <td>108</td>\n",
       "      <td>2019-06-15</td>\n",
       "      <td>1.11</td>\n",
       "      <td>3</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>9657</td>\n",
       "      <td>Modern 1 BR / NYC / EAST VILLAGE</td>\n",
       "      <td>21904</td>\n",
       "      <td>Dana</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Village</td>\n",
       "      <td>40.72920</td>\n",
       "      <td>-73.98542</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>180</td>\n",
       "      <td>14</td>\n",
       "      <td>29</td>\n",
       "      <td>2019-04-19</td>\n",
       "      <td>0.24</td>\n",
       "      <td>1</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48865</th>\n",
       "      <td>36472171</td>\n",
       "      <td>1 bedroom in sunlit apartment</td>\n",
       "      <td>99144947</td>\n",
       "      <td>Brenda</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Inwood</td>\n",
       "      <td>40.86845</td>\n",
       "      <td>-73.92449</td>\n",
       "      <td>Private room</td>\n",
       "      <td>80</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48866</th>\n",
       "      <td>36472710</td>\n",
       "      <td>CozyHideAway Suite</td>\n",
       "      <td>274225617</td>\n",
       "      <td>Alberth</td>\n",
       "      <td>Queens</td>\n",
       "      <td>Briarwood</td>\n",
       "      <td>40.70786</td>\n",
       "      <td>-73.81448</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>58</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48867</th>\n",
       "      <td>36473044</td>\n",
       "      <td>The place you were dreaming for.(only for guys)</td>\n",
       "      <td>261338177</td>\n",
       "      <td>Diana</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Gravesend</td>\n",
       "      <td>40.59080</td>\n",
       "      <td>-73.97116</td>\n",
       "      <td>Shared room</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48868</th>\n",
       "      <td>36473253</td>\n",
       "      <td>Heaven for you(only for guy)</td>\n",
       "      <td>261338177</td>\n",
       "      <td>Diana</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Gravesend</td>\n",
       "      <td>40.59118</td>\n",
       "      <td>-73.97119</td>\n",
       "      <td>Shared room</td>\n",
       "      <td>25</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48869</th>\n",
       "      <td>36474023</td>\n",
       "      <td>Cozy, Sunny Brooklyn Escape</td>\n",
       "      <td>1550580</td>\n",
       "      <td>Julia</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bedford-Stuyvesant</td>\n",
       "      <td>40.68759</td>\n",
       "      <td>-73.95705</td>\n",
       "      <td>Private room</td>\n",
       "      <td>45</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48870</th>\n",
       "      <td>36474911</td>\n",
       "      <td>Cozy, clean Williamsburg 1- bedroom apartment</td>\n",
       "      <td>1273444</td>\n",
       "      <td>Tanja</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71197</td>\n",
       "      <td>-73.94946</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>99</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48871</th>\n",
       "      <td>36475746</td>\n",
       "      <td>A LARGE ROOM - 1 MONTH MINIMUM - WASHER&amp;DRYER</td>\n",
       "      <td>144008701</td>\n",
       "      <td>Ozzy Ciao</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.82233</td>\n",
       "      <td>-73.94687</td>\n",
       "      <td>Private room</td>\n",
       "      <td>35</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48872</th>\n",
       "      <td>36476675</td>\n",
       "      <td>Nycity-MyHome</td>\n",
       "      <td>8636072</td>\n",
       "      <td>Ben</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hell's Kitchen</td>\n",
       "      <td>40.76236</td>\n",
       "      <td>-73.99255</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>260</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48873</th>\n",
       "      <td>36477307</td>\n",
       "      <td>Brooklyn paradise</td>\n",
       "      <td>241945355</td>\n",
       "      <td>Clement &amp; Rose</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Flatlands</td>\n",
       "      <td>40.63116</td>\n",
       "      <td>-73.92616</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>170</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48874</th>\n",
       "      <td>36477588</td>\n",
       "      <td>Short Term Rental in East Harlem</td>\n",
       "      <td>214535893</td>\n",
       "      <td>Jeffrey</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.79760</td>\n",
       "      <td>-73.93947</td>\n",
       "      <td>Private room</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48875</th>\n",
       "      <td>36478343</td>\n",
       "      <td>Welcome all as family</td>\n",
       "      <td>274273284</td>\n",
       "      <td>Anastasia</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.78749</td>\n",
       "      <td>-73.94749</td>\n",
       "      <td>Private room</td>\n",
       "      <td>140</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48876</th>\n",
       "      <td>36478357</td>\n",
       "      <td>Cozy, Air-Conditioned Private Bedroom in Harlem</td>\n",
       "      <td>177932088</td>\n",
       "      <td>Joseph</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.80953</td>\n",
       "      <td>-73.95410</td>\n",
       "      <td>Private room</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48877</th>\n",
       "      <td>36479230</td>\n",
       "      <td>Studio sized room with beautiful light</td>\n",
       "      <td>65767720</td>\n",
       "      <td>Melanie</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick</td>\n",
       "      <td>40.70418</td>\n",
       "      <td>-73.91471</td>\n",
       "      <td>Private room</td>\n",
       "      <td>42</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48878</th>\n",
       "      <td>36479723</td>\n",
       "      <td>Room for rest</td>\n",
       "      <td>41326856</td>\n",
       "      <td>Jeerathinan</td>\n",
       "      <td>Queens</td>\n",
       "      <td>Elmhurst</td>\n",
       "      <td>40.74477</td>\n",
       "      <td>-73.87727</td>\n",
       "      <td>Private room</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48879</th>\n",
       "      <td>36480292</td>\n",
       "      <td>Gorgeous 1.5 Bdr with a private yard- Williams...</td>\n",
       "      <td>540335</td>\n",
       "      <td>Lee</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71728</td>\n",
       "      <td>-73.94394</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48880</th>\n",
       "      <td>36481315</td>\n",
       "      <td>The Raccoon Artist Studio in Williamsburg New ...</td>\n",
       "      <td>208514239</td>\n",
       "      <td>Melki</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71232</td>\n",
       "      <td>-73.94220</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48881</th>\n",
       "      <td>36481615</td>\n",
       "      <td>Peaceful space in Greenpoint, BK</td>\n",
       "      <td>274298453</td>\n",
       "      <td>Adrien</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Greenpoint</td>\n",
       "      <td>40.72585</td>\n",
       "      <td>-73.94001</td>\n",
       "      <td>Private room</td>\n",
       "      <td>54</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48882</th>\n",
       "      <td>36482231</td>\n",
       "      <td>Bushwick _ Myrtle-Wyckoff</td>\n",
       "      <td>66058896</td>\n",
       "      <td>Luisa</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick</td>\n",
       "      <td>40.69652</td>\n",
       "      <td>-73.91079</td>\n",
       "      <td>Private room</td>\n",
       "      <td>40</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48883</th>\n",
       "      <td>36482416</td>\n",
       "      <td>Sunny Bedroom NYC! Walking to Central Park!!</td>\n",
       "      <td>131529729</td>\n",
       "      <td>Kendall</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.79755</td>\n",
       "      <td>-73.93614</td>\n",
       "      <td>Private room</td>\n",
       "      <td>75</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48884</th>\n",
       "      <td>36482783</td>\n",
       "      <td>Brooklyn Oasis in the heart of Williamsburg</td>\n",
       "      <td>274307600</td>\n",
       "      <td>Jonathan</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71790</td>\n",
       "      <td>-73.96238</td>\n",
       "      <td>Private room</td>\n",
       "      <td>190</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48885</th>\n",
       "      <td>36482809</td>\n",
       "      <td>Stunning Bedroom NYC! Walking to Central Park!!</td>\n",
       "      <td>131529729</td>\n",
       "      <td>Kendall</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.79633</td>\n",
       "      <td>-73.93605</td>\n",
       "      <td>Private room</td>\n",
       "      <td>75</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48886</th>\n",
       "      <td>36483010</td>\n",
       "      <td>Comfy 1 Bedroom in Midtown East</td>\n",
       "      <td>274311461</td>\n",
       "      <td>Scott</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Midtown</td>\n",
       "      <td>40.75561</td>\n",
       "      <td>-73.96723</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>200</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48887</th>\n",
       "      <td>36483152</td>\n",
       "      <td>Garden Jewel Apartment in Williamsburg New York</td>\n",
       "      <td>208514239</td>\n",
       "      <td>Melki</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71232</td>\n",
       "      <td>-73.94220</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>170</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48888</th>\n",
       "      <td>36484087</td>\n",
       "      <td>Spacious Room w/ Private Rooftop, Central loca...</td>\n",
       "      <td>274321313</td>\n",
       "      <td>Kat</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hell's Kitchen</td>\n",
       "      <td>40.76392</td>\n",
       "      <td>-73.99183</td>\n",
       "      <td>Private room</td>\n",
       "      <td>125</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48889</th>\n",
       "      <td>36484363</td>\n",
       "      <td>QUIT PRIVATE HOUSE</td>\n",
       "      <td>107716952</td>\n",
       "      <td>Michael</td>\n",
       "      <td>Queens</td>\n",
       "      <td>Jamaica</td>\n",
       "      <td>40.69137</td>\n",
       "      <td>-73.80844</td>\n",
       "      <td>Private room</td>\n",
       "      <td>65</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48890</th>\n",
       "      <td>36484665</td>\n",
       "      <td>Charming one bedroom - newly renovated rowhouse</td>\n",
       "      <td>8232441</td>\n",
       "      <td>Sabrina</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bedford-Stuyvesant</td>\n",
       "      <td>40.67853</td>\n",
       "      <td>-73.94995</td>\n",
       "      <td>Private room</td>\n",
       "      <td>70</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48891</th>\n",
       "      <td>36485057</td>\n",
       "      <td>Affordable room in Bushwick/East Williamsburg</td>\n",
       "      <td>6570630</td>\n",
       "      <td>Marisol</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick</td>\n",
       "      <td>40.70184</td>\n",
       "      <td>-73.93317</td>\n",
       "      <td>Private room</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48892</th>\n",
       "      <td>36485431</td>\n",
       "      <td>Sunny Studio at Historical Neighborhood</td>\n",
       "      <td>23492952</td>\n",
       "      <td>Ilgar &amp; Aysel</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.81475</td>\n",
       "      <td>-73.94867</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>115</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48893</th>\n",
       "      <td>36485609</td>\n",
       "      <td>43rd St. Time Square-cozy single bed</td>\n",
       "      <td>30985759</td>\n",
       "      <td>Taz</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hell's Kitchen</td>\n",
       "      <td>40.75751</td>\n",
       "      <td>-73.99112</td>\n",
       "      <td>Shared room</td>\n",
       "      <td>55</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48894</th>\n",
       "      <td>36487245</td>\n",
       "      <td>Trendy duplex in the very heart of Hell's Kitchen</td>\n",
       "      <td>68119814</td>\n",
       "      <td>Christophe</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hell's Kitchen</td>\n",
       "      <td>40.76404</td>\n",
       "      <td>-73.98933</td>\n",
       "      <td>Private room</td>\n",
       "      <td>90</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>48895 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id                                               name    host_id  \\\n",
       "0          2539                 Clean & quiet apt home by the park       2787   \n",
       "1          2595                              Skylit Midtown Castle       2845   \n",
       "2          3647                THE VILLAGE OF HARLEM....NEW YORK !       4632   \n",
       "3          3831                    Cozy Entire Floor of Brownstone       4869   \n",
       "4          5022   Entire Apt: Spacious Studio/Loft by central park       7192   \n",
       "5          5099          Large Cozy 1 BR Apartment In Midtown East       7322   \n",
       "6          5121                                    BlissArtsSpace!       7356   \n",
       "7          5178                   Large Furnished Room Near B'way        8967   \n",
       "8          5203                 Cozy Clean Guest Room - Family Apt       7490   \n",
       "9          5238                 Cute & Cozy Lower East Side 1 bdrm       7549   \n",
       "10         5295                   Beautiful 1br on Upper West Side       7702   \n",
       "11         5441                    Central Manhattan/near Broadway       7989   \n",
       "12         5803     Lovely Room 1, Garden, Best Area, Legal rental       9744   \n",
       "13         6021   Wonderful Guest Bedroom in Manhattan for SINGLES      11528   \n",
       "14         6090                      West Village Nest - Superhost      11975   \n",
       "15         6848                   Only 2 stops to Manhattan studio      15991   \n",
       "16         7097                  Perfect for Your Parents + Garden      17571   \n",
       "17         7322                                    Chelsea Perfect      18946   \n",
       "18         7726    Hip Historic Brownstone Apartment with Backyard      20950   \n",
       "19         7750                  Huge 2 BR Upper East  Cental Park      17985   \n",
       "20         7801                   Sweet and Spacious Brooklyn Loft      21207   \n",
       "21         8024                     CBG CtyBGd HelpsHaiti rm#1:1-4      22486   \n",
       "22         8025                           CBG Helps Haiti Room#2.5      22486   \n",
       "23         8110                              CBG Helps Haiti Rm #2      22486   \n",
       "24         8490             MAISON DES SIRENES1,bohemian apartment      25183   \n",
       "25         8505                 Sunny Bedroom Across Prospect Park      25326   \n",
       "26         8700  Magnifique Suite au N de Manhattan - vue Cloitres      26394   \n",
       "27         9357                               Midtown Pied-a-terre      30193   \n",
       "28         9518       SPACIOUS, LOVELY FURNISHED MANHATTAN BEDROOM      31374   \n",
       "29         9657                   Modern 1 BR / NYC / EAST VILLAGE      21904   \n",
       "...         ...                                                ...        ...   \n",
       "48865  36472171                      1 bedroom in sunlit apartment   99144947   \n",
       "48866  36472710                                 CozyHideAway Suite  274225617   \n",
       "48867  36473044    The place you were dreaming for.(only for guys)  261338177   \n",
       "48868  36473253                       Heaven for you(only for guy)  261338177   \n",
       "48869  36474023                        Cozy, Sunny Brooklyn Escape    1550580   \n",
       "48870  36474911      Cozy, clean Williamsburg 1- bedroom apartment    1273444   \n",
       "48871  36475746      A LARGE ROOM - 1 MONTH MINIMUM - WASHER&DRYER  144008701   \n",
       "48872  36476675                                      Nycity-MyHome    8636072   \n",
       "48873  36477307                                  Brooklyn paradise  241945355   \n",
       "48874  36477588                   Short Term Rental in East Harlem  214535893   \n",
       "48875  36478343                              Welcome all as family  274273284   \n",
       "48876  36478357    Cozy, Air-Conditioned Private Bedroom in Harlem  177932088   \n",
       "48877  36479230             Studio sized room with beautiful light   65767720   \n",
       "48878  36479723                                      Room for rest   41326856   \n",
       "48879  36480292  Gorgeous 1.5 Bdr with a private yard- Williams...     540335   \n",
       "48880  36481315  The Raccoon Artist Studio in Williamsburg New ...  208514239   \n",
       "48881  36481615                   Peaceful space in Greenpoint, BK  274298453   \n",
       "48882  36482231                          Bushwick _ Myrtle-Wyckoff   66058896   \n",
       "48883  36482416       Sunny Bedroom NYC! Walking to Central Park!!  131529729   \n",
       "48884  36482783        Brooklyn Oasis in the heart of Williamsburg  274307600   \n",
       "48885  36482809    Stunning Bedroom NYC! Walking to Central Park!!  131529729   \n",
       "48886  36483010                    Comfy 1 Bedroom in Midtown East  274311461   \n",
       "48887  36483152    Garden Jewel Apartment in Williamsburg New York  208514239   \n",
       "48888  36484087  Spacious Room w/ Private Rooftop, Central loca...  274321313   \n",
       "48889  36484363                                 QUIT PRIVATE HOUSE  107716952   \n",
       "48890  36484665    Charming one bedroom - newly renovated rowhouse    8232441   \n",
       "48891  36485057      Affordable room in Bushwick/East Williamsburg    6570630   \n",
       "48892  36485431            Sunny Studio at Historical Neighborhood   23492952   \n",
       "48893  36485609               43rd St. Time Square-cozy single bed   30985759   \n",
       "48894  36487245  Trendy duplex in the very heart of Hell's Kitchen   68119814   \n",
       "\n",
       "              host_name neighbourhood_group       neighbourhood  latitude  \\\n",
       "0                  John            Brooklyn          Kensington  40.64749   \n",
       "1              Jennifer           Manhattan             Midtown  40.75362   \n",
       "2             Elisabeth           Manhattan              Harlem  40.80902   \n",
       "3           LisaRoxanne            Brooklyn        Clinton Hill  40.68514   \n",
       "4                 Laura           Manhattan         East Harlem  40.79851   \n",
       "5                 Chris           Manhattan         Murray Hill  40.74767   \n",
       "6                 Garon            Brooklyn  Bedford-Stuyvesant  40.68688   \n",
       "7              Shunichi           Manhattan      Hell's Kitchen  40.76489   \n",
       "8             MaryEllen           Manhattan     Upper West Side  40.80178   \n",
       "9                   Ben           Manhattan           Chinatown  40.71344   \n",
       "10                 Lena           Manhattan     Upper West Side  40.80316   \n",
       "11                 Kate           Manhattan      Hell's Kitchen  40.76076   \n",
       "12               Laurie            Brooklyn         South Slope  40.66829   \n",
       "13              Claudio           Manhattan     Upper West Side  40.79826   \n",
       "14                Alina           Manhattan        West Village  40.73530   \n",
       "15        Allen & Irina            Brooklyn        Williamsburg  40.70837   \n",
       "16                 Jane            Brooklyn         Fort Greene  40.69169   \n",
       "17                 Doti           Manhattan             Chelsea  40.74192   \n",
       "18     Adam And Charity            Brooklyn       Crown Heights  40.67592   \n",
       "19                 Sing           Manhattan         East Harlem  40.79685   \n",
       "20                Chaya            Brooklyn        Williamsburg  40.71842   \n",
       "21                Lisel            Brooklyn          Park Slope  40.68069   \n",
       "22                Lisel            Brooklyn          Park Slope  40.67989   \n",
       "23                Lisel            Brooklyn          Park Slope  40.68001   \n",
       "24             Nathalie            Brooklyn  Bedford-Stuyvesant  40.68371   \n",
       "25              Gregory            Brooklyn     Windsor Terrace  40.65599   \n",
       "26      Claude & Sophie           Manhattan              Inwood  40.86754   \n",
       "27                Tommi           Manhattan      Hell's Kitchen  40.76715   \n",
       "28                 Shon           Manhattan              Inwood  40.86482   \n",
       "29                 Dana           Manhattan        East Village  40.72920   \n",
       "...                 ...                 ...                 ...       ...   \n",
       "48865            Brenda           Manhattan              Inwood  40.86845   \n",
       "48866           Alberth              Queens           Briarwood  40.70786   \n",
       "48867             Diana            Brooklyn           Gravesend  40.59080   \n",
       "48868             Diana            Brooklyn           Gravesend  40.59118   \n",
       "48869             Julia            Brooklyn  Bedford-Stuyvesant  40.68759   \n",
       "48870             Tanja            Brooklyn        Williamsburg  40.71197   \n",
       "48871         Ozzy Ciao           Manhattan              Harlem  40.82233   \n",
       "48872               Ben           Manhattan      Hell's Kitchen  40.76236   \n",
       "48873    Clement & Rose            Brooklyn           Flatlands  40.63116   \n",
       "48874           Jeffrey           Manhattan         East Harlem  40.79760   \n",
       "48875         Anastasia           Manhattan         East Harlem  40.78749   \n",
       "48876            Joseph           Manhattan              Harlem  40.80953   \n",
       "48877           Melanie            Brooklyn            Bushwick  40.70418   \n",
       "48878       Jeerathinan              Queens            Elmhurst  40.74477   \n",
       "48879               Lee            Brooklyn        Williamsburg  40.71728   \n",
       "48880             Melki            Brooklyn        Williamsburg  40.71232   \n",
       "48881            Adrien            Brooklyn          Greenpoint  40.72585   \n",
       "48882             Luisa            Brooklyn            Bushwick  40.69652   \n",
       "48883           Kendall           Manhattan         East Harlem  40.79755   \n",
       "48884          Jonathan            Brooklyn        Williamsburg  40.71790   \n",
       "48885           Kendall           Manhattan         East Harlem  40.79633   \n",
       "48886             Scott           Manhattan             Midtown  40.75561   \n",
       "48887             Melki            Brooklyn        Williamsburg  40.71232   \n",
       "48888               Kat           Manhattan      Hell's Kitchen  40.76392   \n",
       "48889           Michael              Queens             Jamaica  40.69137   \n",
       "48890           Sabrina            Brooklyn  Bedford-Stuyvesant  40.67853   \n",
       "48891           Marisol            Brooklyn            Bushwick  40.70184   \n",
       "48892     Ilgar & Aysel           Manhattan              Harlem  40.81475   \n",
       "48893               Taz           Manhattan      Hell's Kitchen  40.75751   \n",
       "48894        Christophe           Manhattan      Hell's Kitchen  40.76404   \n",
       "\n",
       "       longitude        room_type  price  minimum_nights  number_of_reviews  \\\n",
       "0      -73.97237     Private room    149               1                  9   \n",
       "1      -73.98377  Entire home/apt    225               1                 45   \n",
       "2      -73.94190     Private room    150               3                  0   \n",
       "3      -73.95976  Entire home/apt     89               1                270   \n",
       "4      -73.94399  Entire home/apt     80              10                  9   \n",
       "5      -73.97500  Entire home/apt    200               3                 74   \n",
       "6      -73.95596     Private room     60              45                 49   \n",
       "7      -73.98493     Private room     79               2                430   \n",
       "8      -73.96723     Private room     79               2                118   \n",
       "9      -73.99037  Entire home/apt    150               1                160   \n",
       "10     -73.96545  Entire home/apt    135               5                 53   \n",
       "11     -73.98867     Private room     85               2                188   \n",
       "12     -73.98779     Private room     89               4                167   \n",
       "13     -73.96113     Private room     85               2                113   \n",
       "14     -74.00525  Entire home/apt    120              90                 27   \n",
       "15     -73.95352  Entire home/apt    140               2                148   \n",
       "16     -73.97185  Entire home/apt    215               2                198   \n",
       "17     -73.99501     Private room    140               1                260   \n",
       "18     -73.94694  Entire home/apt     99               3                 53   \n",
       "19     -73.94872  Entire home/apt    190               7                  0   \n",
       "20     -73.95718  Entire home/apt    299               3                  9   \n",
       "21     -73.97706     Private room    130               2                130   \n",
       "22     -73.97798     Private room     80               1                 39   \n",
       "23     -73.97865     Private room    110               2                 71   \n",
       "24     -73.94028  Entire home/apt    120               2                 88   \n",
       "25     -73.97519     Private room     60               1                 19   \n",
       "26     -73.92639     Private room     80               4                  0   \n",
       "27     -73.98533  Entire home/apt    150              10                 58   \n",
       "28     -73.92106     Private room     44               3                108   \n",
       "29     -73.98542  Entire home/apt    180              14                 29   \n",
       "...          ...              ...    ...             ...                ...   \n",
       "48865  -73.92449     Private room     80               1                  0   \n",
       "48866  -73.81448  Entire home/apt     58               1                  0   \n",
       "48867  -73.97116      Shared room     25               1                  0   \n",
       "48868  -73.97119      Shared room     25               7                  0   \n",
       "48869  -73.95705     Private room     45               4                  0   \n",
       "48870  -73.94946  Entire home/apt     99               4                  0   \n",
       "48871  -73.94687     Private room     35              29                  0   \n",
       "48872  -73.99255  Entire home/apt    260               3                  0   \n",
       "48873  -73.92616  Entire home/apt    170               1                  0   \n",
       "48874  -73.93947     Private room     50               7                  0   \n",
       "48875  -73.94749     Private room    140               1                  0   \n",
       "48876  -73.95410     Private room     60               1                  0   \n",
       "48877  -73.91471     Private room     42               7                  0   \n",
       "48878  -73.87727     Private room     45               1                  0   \n",
       "48879  -73.94394  Entire home/apt    120              20                  0   \n",
       "48880  -73.94220  Entire home/apt    120               1                  0   \n",
       "48881  -73.94001     Private room     54               6                  0   \n",
       "48882  -73.91079     Private room     40              20                  0   \n",
       "48883  -73.93614     Private room     75               2                  0   \n",
       "48884  -73.96238     Private room    190               7                  0   \n",
       "48885  -73.93605     Private room     75               2                  0   \n",
       "48886  -73.96723  Entire home/apt    200               6                  0   \n",
       "48887  -73.94220  Entire home/apt    170               1                  0   \n",
       "48888  -73.99183     Private room    125               4                  0   \n",
       "48889  -73.80844     Private room     65               1                  0   \n",
       "48890  -73.94995     Private room     70               2                  0   \n",
       "48891  -73.93317     Private room     40               4                  0   \n",
       "48892  -73.94867  Entire home/apt    115              10                  0   \n",
       "48893  -73.99112      Shared room     55               1                  0   \n",
       "48894  -73.98933     Private room     90               7                  0   \n",
       "\n",
       "      last_review  reviews_per_month  calculated_host_listings_count  \\\n",
       "0      2018-10-19               0.21                               6   \n",
       "1      2019-05-21               0.38                               2   \n",
       "2             NaN                NaN                               1   \n",
       "3      2019-07-05               4.64                               1   \n",
       "4      2018-11-19               0.10                               1   \n",
       "5      2019-06-22               0.59                               1   \n",
       "6      2017-10-05               0.40                               1   \n",
       "7      2019-06-24               3.47                               1   \n",
       "8      2017-07-21               0.99                               1   \n",
       "9      2019-06-09               1.33                               4   \n",
       "10     2019-06-22               0.43                               1   \n",
       "11     2019-06-23               1.50                               1   \n",
       "12     2019-06-24               1.34                               3   \n",
       "13     2019-07-05               0.91                               1   \n",
       "14     2018-10-31               0.22                               1   \n",
       "15     2019-06-29               1.20                               1   \n",
       "16     2019-06-28               1.72                               1   \n",
       "17     2019-07-01               2.12                               1   \n",
       "18     2019-06-22               4.44                               1   \n",
       "19            NaN                NaN                               2   \n",
       "20     2011-12-28               0.07                               1   \n",
       "21     2019-07-01               1.09                               6   \n",
       "22     2019-01-01               0.37                               6   \n",
       "23     2019-07-02               0.61                               6   \n",
       "24     2019-06-19               0.73                               2   \n",
       "25     2019-06-23               1.37                               2   \n",
       "26            NaN                NaN                               1   \n",
       "27     2017-08-13               0.49                               1   \n",
       "28     2019-06-15               1.11                               3   \n",
       "29     2019-04-19               0.24                               1   \n",
       "...           ...                ...                             ...   \n",
       "48865         NaN                NaN                               1   \n",
       "48866         NaN                NaN                               1   \n",
       "48867         NaN                NaN                               6   \n",
       "48868         NaN                NaN                               6   \n",
       "48869         NaN                NaN                               1   \n",
       "48870         NaN                NaN                               1   \n",
       "48871         NaN                NaN                               2   \n",
       "48872         NaN                NaN                               1   \n",
       "48873         NaN                NaN                               2   \n",
       "48874         NaN                NaN                               1   \n",
       "48875         NaN                NaN                               1   \n",
       "48876         NaN                NaN                               1   \n",
       "48877         NaN                NaN                               1   \n",
       "48878         NaN                NaN                               5   \n",
       "48879         NaN                NaN                               1   \n",
       "48880         NaN                NaN                               3   \n",
       "48881         NaN                NaN                               1   \n",
       "48882         NaN                NaN                               1   \n",
       "48883         NaN                NaN                               2   \n",
       "48884         NaN                NaN                               1   \n",
       "48885         NaN                NaN                               2   \n",
       "48886         NaN                NaN                               1   \n",
       "48887         NaN                NaN                               3   \n",
       "48888         NaN                NaN                               1   \n",
       "48889         NaN                NaN                               2   \n",
       "48890         NaN                NaN                               2   \n",
       "48891         NaN                NaN                               2   \n",
       "48892         NaN                NaN                               1   \n",
       "48893         NaN                NaN                               6   \n",
       "48894         NaN                NaN                               1   \n",
       "\n",
       "       availability_365  \n",
       "0                   365  \n",
       "1                   355  \n",
       "2                   365  \n",
       "3                   194  \n",
       "4                     0  \n",
       "5                   129  \n",
       "6                     0  \n",
       "7                   220  \n",
       "8                     0  \n",
       "9                   188  \n",
       "10                    6  \n",
       "11                   39  \n",
       "12                  314  \n",
       "13                  333  \n",
       "14                    0  \n",
       "15                   46  \n",
       "16                  321  \n",
       "17                   12  \n",
       "18                   21  \n",
       "19                  249  \n",
       "20                    0  \n",
       "21                  347  \n",
       "22                  364  \n",
       "23                  304  \n",
       "24                  233  \n",
       "25                   85  \n",
       "26                    0  \n",
       "27                   75  \n",
       "28                  311  \n",
       "29                   67  \n",
       "...                 ...  \n",
       "48865                79  \n",
       "48866               159  \n",
       "48867               338  \n",
       "48868               365  \n",
       "48869                 7  \n",
       "48870                22  \n",
       "48871                31  \n",
       "48872                 9  \n",
       "48873               363  \n",
       "48874                22  \n",
       "48875               180  \n",
       "48876                26  \n",
       "48877                16  \n",
       "48878               172  \n",
       "48879                22  \n",
       "48880               365  \n",
       "48881                15  \n",
       "48882                31  \n",
       "48883               364  \n",
       "48884               341  \n",
       "48885               353  \n",
       "48886               176  \n",
       "48887               365  \n",
       "48888                31  \n",
       "48889               163  \n",
       "48890                 9  \n",
       "48891                36  \n",
       "48892                27  \n",
       "48893                 2  \n",
       "48894                23  \n",
       "\n",
       "[48895 rows x 16 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"airbnb/complete.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Activity 2: data exploration with pandas\n",
    "\n",
    "<img src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Antu_task-complete.svg/1024px-Antu_task-complete.svg.png\" width=50 align=left/>\n",
    "\n",
    "* Import the (full) AirBnb dataset as a Pandas dataframe\n",
    "* Try the following functions and check what they do: \n",
    "    * `df.head()`\n",
    "    * `df.describe()`\n",
    "    * `df[\"price\"]`\n",
    "    * `df[3]`\n",
    "    * `df.sort_values(by='price')`\n",
    "    * `df[df.price > 100]`\n",
    "    * `(df[\"price\"] > 100) & (df[\"price\"] < 150)`\n",
    "    * `df.query(\"price > 100 and price < 150\")`\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>host_id</th>\n",
       "      <th>host_name</th>\n",
       "      <th>neighbourhood_group</th>\n",
       "      <th>neighbourhood</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>room_type</th>\n",
       "      <th>price</th>\n",
       "      <th>minimum_nights</th>\n",
       "      <th>number_of_reviews</th>\n",
       "      <th>last_review</th>\n",
       "      <th>reviews_per_month</th>\n",
       "      <th>calculated_host_listings_count</th>\n",
       "      <th>availability_365</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2539</td>\n",
       "      <td>Clean &amp; quiet apt home by the park</td>\n",
       "      <td>2787</td>\n",
       "      <td>John</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Kensington</td>\n",
       "      <td>40.64749</td>\n",
       "      <td>-73.97237</td>\n",
       "      <td>Private room</td>\n",
       "      <td>149</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>2018-10-19</td>\n",
       "      <td>0.21</td>\n",
       "      <td>6</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5295</td>\n",
       "      <td>Beautiful 1br on Upper West Side</td>\n",
       "      <td>7702</td>\n",
       "      <td>Lena</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>40.80316</td>\n",
       "      <td>-73.96545</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>135</td>\n",
       "      <td>5</td>\n",
       "      <td>53</td>\n",
       "      <td>2019-06-22</td>\n",
       "      <td>0.43</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>6090</td>\n",
       "      <td>West Village Nest - Superhost</td>\n",
       "      <td>11975</td>\n",
       "      <td>Alina</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>West Village</td>\n",
       "      <td>40.73530</td>\n",
       "      <td>-74.00525</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>90</td>\n",
       "      <td>27</td>\n",
       "      <td>2018-10-31</td>\n",
       "      <td>0.22</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>6848</td>\n",
       "      <td>Only 2 stops to Manhattan studio</td>\n",
       "      <td>15991</td>\n",
       "      <td>Allen &amp; Irina</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.70837</td>\n",
       "      <td>-73.95352</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>140</td>\n",
       "      <td>2</td>\n",
       "      <td>148</td>\n",
       "      <td>2019-06-29</td>\n",
       "      <td>1.20</td>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>7322</td>\n",
       "      <td>Chelsea Perfect</td>\n",
       "      <td>18946</td>\n",
       "      <td>Doti</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>40.74192</td>\n",
       "      <td>-73.99501</td>\n",
       "      <td>Private room</td>\n",
       "      <td>140</td>\n",
       "      <td>1</td>\n",
       "      <td>260</td>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>2.12</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>8024</td>\n",
       "      <td>CBG CtyBGd HelpsHaiti rm#1:1-4</td>\n",
       "      <td>22486</td>\n",
       "      <td>Lisel</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Park Slope</td>\n",
       "      <td>40.68069</td>\n",
       "      <td>-73.97706</td>\n",
       "      <td>Private room</td>\n",
       "      <td>130</td>\n",
       "      <td>2</td>\n",
       "      <td>130</td>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>1.09</td>\n",
       "      <td>6</td>\n",
       "      <td>347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>8110</td>\n",
       "      <td>CBG Helps Haiti Rm #2</td>\n",
       "      <td>22486</td>\n",
       "      <td>Lisel</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Park Slope</td>\n",
       "      <td>40.68001</td>\n",
       "      <td>-73.97865</td>\n",
       "      <td>Private room</td>\n",
       "      <td>110</td>\n",
       "      <td>2</td>\n",
       "      <td>71</td>\n",
       "      <td>2019-07-02</td>\n",
       "      <td>0.61</td>\n",
       "      <td>6</td>\n",
       "      <td>304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>8490</td>\n",
       "      <td>MAISON DES SIRENES1,bohemian apartment</td>\n",
       "      <td>25183</td>\n",
       "      <td>Nathalie</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bedford-Stuyvesant</td>\n",
       "      <td>40.68371</td>\n",
       "      <td>-73.94028</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>2</td>\n",
       "      <td>88</td>\n",
       "      <td>2019-06-19</td>\n",
       "      <td>0.73</td>\n",
       "      <td>2</td>\n",
       "      <td>233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>12299</td>\n",
       "      <td>Beautiful Sunny Park Slope Brooklyn</td>\n",
       "      <td>47610</td>\n",
       "      <td>Abdul</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>South Slope</td>\n",
       "      <td>40.66278</td>\n",
       "      <td>-73.97966</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>0.39</td>\n",
       "      <td>1</td>\n",
       "      <td>345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>12303</td>\n",
       "      <td>1bdr w private bath. in lofty apt</td>\n",
       "      <td>47618</td>\n",
       "      <td>Yolande</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Fort Greene</td>\n",
       "      <td>40.69673</td>\n",
       "      <td>-73.97584</td>\n",
       "      <td>Private room</td>\n",
       "      <td>120</td>\n",
       "      <td>7</td>\n",
       "      <td>25</td>\n",
       "      <td>2018-09-30</td>\n",
       "      <td>0.23</td>\n",
       "      <td>1</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>12318</td>\n",
       "      <td>West Side Retreat</td>\n",
       "      <td>16800</td>\n",
       "      <td>Cyn</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>40.79009</td>\n",
       "      <td>-73.97927</td>\n",
       "      <td>Private room</td>\n",
       "      <td>135</td>\n",
       "      <td>4</td>\n",
       "      <td>81</td>\n",
       "      <td>2019-06-16</td>\n",
       "      <td>0.69</td>\n",
       "      <td>1</td>\n",
       "      <td>273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>12937</td>\n",
       "      <td>1 Stop fr. Manhattan! Private Suite,Landmark B...</td>\n",
       "      <td>50124</td>\n",
       "      <td>Orestes</td>\n",
       "      <td>Queens</td>\n",
       "      <td>Long Island City</td>\n",
       "      <td>40.74771</td>\n",
       "      <td>-73.94740</td>\n",
       "      <td>Private room</td>\n",
       "      <td>130</td>\n",
       "      <td>3</td>\n",
       "      <td>248</td>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>2.25</td>\n",
       "      <td>1</td>\n",
       "      <td>215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>12940</td>\n",
       "      <td>Charming Brownstone 3 - Near PRATT</td>\n",
       "      <td>50148</td>\n",
       "      <td>Adreinne</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bedford-Stuyvesant</td>\n",
       "      <td>40.68111</td>\n",
       "      <td>-73.95591</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>110</td>\n",
       "      <td>7</td>\n",
       "      <td>61</td>\n",
       "      <td>2019-05-25</td>\n",
       "      <td>0.52</td>\n",
       "      <td>1</td>\n",
       "      <td>265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>13050</td>\n",
       "      <td>bright and stylish duplex</td>\n",
       "      <td>50846</td>\n",
       "      <td>Jennifer</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bedford-Stuyvesant</td>\n",
       "      <td>40.68554</td>\n",
       "      <td>-73.94090</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>115</td>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>14314</td>\n",
       "      <td>Greenpoint Place...Has It All!</td>\n",
       "      <td>56246</td>\n",
       "      <td>Jeanne</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Greenpoint</td>\n",
       "      <td>40.73506</td>\n",
       "      <td>-73.95392</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>144</td>\n",
       "      <td>2</td>\n",
       "      <td>328</td>\n",
       "      <td>2019-06-29</td>\n",
       "      <td>2.82</td>\n",
       "      <td>1</td>\n",
       "      <td>234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>14991</td>\n",
       "      <td>Great Location, Manhattan Bedroom!</td>\n",
       "      <td>59023</td>\n",
       "      <td>Bianca</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Lower East Side</td>\n",
       "      <td>40.72004</td>\n",
       "      <td>-73.99104</td>\n",
       "      <td>Private room</td>\n",
       "      <td>110</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>2019-05-18</td>\n",
       "      <td>0.17</td>\n",
       "      <td>1</td>\n",
       "      <td>301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>17747</td>\n",
       "      <td>BLUE TRIM GUEST HOUSE</td>\n",
       "      <td>68599</td>\n",
       "      <td>George</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Clinton Hill</td>\n",
       "      <td>40.68346</td>\n",
       "      <td>-73.96374</td>\n",
       "      <td>Private room</td>\n",
       "      <td>105</td>\n",
       "      <td>2</td>\n",
       "      <td>105</td>\n",
       "      <td>2019-06-26</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1</td>\n",
       "      <td>304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>18764</td>\n",
       "      <td>Cozy 2 BR in Williamsburg</td>\n",
       "      <td>72014</td>\n",
       "      <td>Lulú</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71154</td>\n",
       "      <td>-73.96112</td>\n",
       "      <td>Private room</td>\n",
       "      <td>145</td>\n",
       "      <td>3</td>\n",
       "      <td>61</td>\n",
       "      <td>2019-04-22</td>\n",
       "      <td>0.54</td>\n",
       "      <td>4</td>\n",
       "      <td>238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>19159</td>\n",
       "      <td>Spacious luminous apt Upper West NYC</td>\n",
       "      <td>73051</td>\n",
       "      <td>Sybilla</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.82915</td>\n",
       "      <td>-73.95136</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>110</td>\n",
       "      <td>31</td>\n",
       "      <td>54</td>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>0.49</td>\n",
       "      <td>1</td>\n",
       "      <td>209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>19282</td>\n",
       "      <td>Sunny, Spacious Top Floor Haven</td>\n",
       "      <td>73469</td>\n",
       "      <td>Gaia</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Flatbush</td>\n",
       "      <td>40.65401</td>\n",
       "      <td>-73.96323</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>130</td>\n",
       "      <td>6</td>\n",
       "      <td>16</td>\n",
       "      <td>2019-06-15</td>\n",
       "      <td>0.15</td>\n",
       "      <td>1</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>19812</td>\n",
       "      <td>2 bedroom Williamsburg Apt - Bedford L stop</td>\n",
       "      <td>74857</td>\n",
       "      <td>Starlee</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71833</td>\n",
       "      <td>-73.95748</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>105</td>\n",
       "      <td>3</td>\n",
       "      <td>61</td>\n",
       "      <td>2018-08-09</td>\n",
       "      <td>0.53</td>\n",
       "      <td>1</td>\n",
       "      <td>272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>20734</td>\n",
       "      <td>Spacious Prospect Heights Apartment</td>\n",
       "      <td>78460</td>\n",
       "      <td>Sean &amp; Lynette</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Prospect Heights</td>\n",
       "      <td>40.68233</td>\n",
       "      <td>-73.97261</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>131</td>\n",
       "      <td>4</td>\n",
       "      <td>166</td>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>3.40</td>\n",
       "      <td>1</td>\n",
       "      <td>207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>21293</td>\n",
       "      <td>Sunny Apartment in Artist Home</td>\n",
       "      <td>44145</td>\n",
       "      <td>Tyrome</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick</td>\n",
       "      <td>40.70093</td>\n",
       "      <td>-73.92609</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>105</td>\n",
       "      <td>3</td>\n",
       "      <td>118</td>\n",
       "      <td>2019-06-18</td>\n",
       "      <td>1.05</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>21456</td>\n",
       "      <td>Light-filled classic Central Park</td>\n",
       "      <td>42032</td>\n",
       "      <td>Dana</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>40.79764</td>\n",
       "      <td>-73.96177</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>140</td>\n",
       "      <td>3</td>\n",
       "      <td>81</td>\n",
       "      <td>2019-07-07</td>\n",
       "      <td>0.71</td>\n",
       "      <td>1</td>\n",
       "      <td>198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>22911</td>\n",
       "      <td>The Stuydio Modern and Light Filled</td>\n",
       "      <td>87773</td>\n",
       "      <td>Shelly</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bedford-Stuyvesant</td>\n",
       "      <td>40.68413</td>\n",
       "      <td>-73.92357</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>125</td>\n",
       "      <td>7</td>\n",
       "      <td>139</td>\n",
       "      <td>2018-10-28</td>\n",
       "      <td>1.23</td>\n",
       "      <td>2</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>24143</td>\n",
       "      <td>Williamsburg—Steps To Subway, Private Bath&amp;Bal...</td>\n",
       "      <td>97219</td>\n",
       "      <td>Seth</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71332</td>\n",
       "      <td>-73.94177</td>\n",
       "      <td>Private room</td>\n",
       "      <td>101</td>\n",
       "      <td>3</td>\n",
       "      <td>335</td>\n",
       "      <td>2019-05-29</td>\n",
       "      <td>3.02</td>\n",
       "      <td>1</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>25235</td>\n",
       "      <td>Large 2 Bedroom Great for Groups!</td>\n",
       "      <td>87773</td>\n",
       "      <td>Shelly</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bedford-Stuyvesant</td>\n",
       "      <td>40.68373</td>\n",
       "      <td>-73.92377</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>125</td>\n",
       "      <td>90</td>\n",
       "      <td>162</td>\n",
       "      <td>2019-06-28</td>\n",
       "      <td>1.46</td>\n",
       "      <td>2</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>26520</td>\n",
       "      <td>Cozy Room #3, Landmark Home 1 Block to PRATT</td>\n",
       "      <td>51038</td>\n",
       "      <td>Erica</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Clinton Hill</td>\n",
       "      <td>40.68698</td>\n",
       "      <td>-73.96572</td>\n",
       "      <td>Private room</td>\n",
       "      <td>125</td>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "      <td>2019-06-02</td>\n",
       "      <td>0.20</td>\n",
       "      <td>6</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>26559</td>\n",
       "      <td>Beautiful Apartment East Village</td>\n",
       "      <td>112793</td>\n",
       "      <td>Sally</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Village</td>\n",
       "      <td>40.72880</td>\n",
       "      <td>-73.98192</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>140</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>2017-12-11</td>\n",
       "      <td>0.13</td>\n",
       "      <td>1</td>\n",
       "      <td>164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>26785</td>\n",
       "      <td>Park Slope Green Guest House</td>\n",
       "      <td>42273</td>\n",
       "      <td>Dani</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>South Slope</td>\n",
       "      <td>40.66853</td>\n",
       "      <td>-73.98912</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>30</td>\n",
       "      <td>467</td>\n",
       "      <td>2018-12-30</td>\n",
       "      <td>4.22</td>\n",
       "      <td>2</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48702</th>\n",
       "      <td>36390301</td>\n",
       "      <td>3 Bedroom Apt in Ridgewood, 20 Min to Manhattan</td>\n",
       "      <td>273632292</td>\n",
       "      <td>Pete</td>\n",
       "      <td>Queens</td>\n",
       "      <td>Ridgewood</td>\n",
       "      <td>40.70268</td>\n",
       "      <td>-73.90353</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>110</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48704</th>\n",
       "      <td>36391474</td>\n",
       "      <td>Wonderful apartment close to Metro</td>\n",
       "      <td>273025497</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Fort Greene</td>\n",
       "      <td>40.68868</td>\n",
       "      <td>-73.97671</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>107</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48706</th>\n",
       "      <td>36391866</td>\n",
       "      <td>Clean, modern, and comfy  1bd apt Manhattan-Ha...</td>\n",
       "      <td>273644177</td>\n",
       "      <td>Merce</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.80078</td>\n",
       "      <td>-73.95079</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>137</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48710</th>\n",
       "      <td>36394726</td>\n",
       "      <td>1 bed available in a 2bd/1ba Bushwick Gem</td>\n",
       "      <td>239638986</td>\n",
       "      <td>Marné</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick</td>\n",
       "      <td>40.69287</td>\n",
       "      <td>-73.92289</td>\n",
       "      <td>Private room</td>\n",
       "      <td>125</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48731</th>\n",
       "      <td>36410519</td>\n",
       "      <td>Sunlight charming apt. in the heart of Brooklyn</td>\n",
       "      <td>121384174</td>\n",
       "      <td>Luciana Paula</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Park Slope</td>\n",
       "      <td>40.66716</td>\n",
       "      <td>-73.98101</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>111</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48736</th>\n",
       "      <td>36412880</td>\n",
       "      <td>Massive Master Bedroom w Private Bathroom</td>\n",
       "      <td>3427758</td>\n",
       "      <td>Phil</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.81274</td>\n",
       "      <td>-73.94357</td>\n",
       "      <td>Private room</td>\n",
       "      <td>110</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48737</th>\n",
       "      <td>36413114</td>\n",
       "      <td>Studio on West 14th Street and 7th Avenue</td>\n",
       "      <td>273772372</td>\n",
       "      <td>Richard</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>West Village</td>\n",
       "      <td>40.73713</td>\n",
       "      <td>-73.99870</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48756</th>\n",
       "      <td>36419441</td>\n",
       "      <td>Murray Hill Masterpiece</td>\n",
       "      <td>273824202</td>\n",
       "      <td>David</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Murray Hill</td>\n",
       "      <td>40.74404</td>\n",
       "      <td>-73.97239</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>129</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48764</th>\n",
       "      <td>36421786</td>\n",
       "      <td>Luxury | Private room |Balcony|Parking included</td>\n",
       "      <td>211500809</td>\n",
       "      <td>Stefania</td>\n",
       "      <td>Queens</td>\n",
       "      <td>Jackson Heights</td>\n",
       "      <td>40.74765</td>\n",
       "      <td>-73.89445</td>\n",
       "      <td>Private room</td>\n",
       "      <td>110</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48765</th>\n",
       "      <td>36421796</td>\n",
       "      <td>Cozy Room with Private Bathroom</td>\n",
       "      <td>273843157</td>\n",
       "      <td>Matheus</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Greenpoint</td>\n",
       "      <td>40.73164</td>\n",
       "      <td>-73.95187</td>\n",
       "      <td>Private room</td>\n",
       "      <td>105</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48767</th>\n",
       "      <td>36422573</td>\n",
       "      <td>Romantic studio in New York artistic best Bush...</td>\n",
       "      <td>273849259</td>\n",
       "      <td>Alexander</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick</td>\n",
       "      <td>40.69958</td>\n",
       "      <td>-73.92772</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48771</th>\n",
       "      <td>36423944</td>\n",
       "      <td>Modern room in luxury apartment</td>\n",
       "      <td>271350187</td>\n",
       "      <td>Elena</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Greenpoint</td>\n",
       "      <td>40.71918</td>\n",
       "      <td>-73.94853</td>\n",
       "      <td>Private room</td>\n",
       "      <td>130</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48776</th>\n",
       "      <td>36424509</td>\n",
       "      <td>Brooklyn Loft : Comfort &amp; Sunset City Views</td>\n",
       "      <td>8411075</td>\n",
       "      <td>Ramiro</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick</td>\n",
       "      <td>40.69608</td>\n",
       "      <td>-73.91210</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>119</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48782</th>\n",
       "      <td>36425863</td>\n",
       "      <td>Lovely Privet Bedroom with Privet Restroom</td>\n",
       "      <td>83554966</td>\n",
       "      <td>Rusaa</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper East Side</td>\n",
       "      <td>40.78099</td>\n",
       "      <td>-73.95366</td>\n",
       "      <td>Private room</td>\n",
       "      <td>129</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2019-07-07</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1</td>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48783</th>\n",
       "      <td>36426093</td>\n",
       "      <td>Best room in nyc</td>\n",
       "      <td>273877318</td>\n",
       "      <td>Jay</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>Claremont Village</td>\n",
       "      <td>40.83926</td>\n",
       "      <td>-73.91173</td>\n",
       "      <td>Private room</td>\n",
       "      <td>140</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48795</th>\n",
       "      <td>36429652</td>\n",
       "      <td>Cute double room for the perfect Yankee fan</td>\n",
       "      <td>58222366</td>\n",
       "      <td>Dominique</td>\n",
       "      <td>Bronx</td>\n",
       "      <td>Claremont Village</td>\n",
       "      <td>40.83502</td>\n",
       "      <td>-73.91058</td>\n",
       "      <td>Private room</td>\n",
       "      <td>125</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48798</th>\n",
       "      <td>36438110</td>\n",
       "      <td>Location! View!  X- Large Studio w/ Washer/Dryer!</td>\n",
       "      <td>96079975</td>\n",
       "      <td>Karen</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper East Side</td>\n",
       "      <td>40.78411</td>\n",
       "      <td>-73.94870</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>140</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48803</th>\n",
       "      <td>36441808</td>\n",
       "      <td>Hell's Kitchen charming apartment</td>\n",
       "      <td>24680496</td>\n",
       "      <td>Miriam</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hell's Kitchen</td>\n",
       "      <td>40.76911</td>\n",
       "      <td>-73.99248</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>145</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48806</th>\n",
       "      <td>36442487</td>\n",
       "      <td>Endless Elegance in Brooklyn</td>\n",
       "      <td>199213364</td>\n",
       "      <td>Eeman</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Sheepshead Bay</td>\n",
       "      <td>40.59731</td>\n",
       "      <td>-73.93381</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>140</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48809</th>\n",
       "      <td>36444734</td>\n",
       "      <td>Sunny Upper West Side Apt. 3mins from Central ...</td>\n",
       "      <td>32987938</td>\n",
       "      <td>Alex</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>40.77889</td>\n",
       "      <td>-73.97668</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>143</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48818</th>\n",
       "      <td>36447795</td>\n",
       "      <td>Beautiful studio Apt. in Harlem (near Red Roos...</td>\n",
       "      <td>274035866</td>\n",
       "      <td>Aurellia</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.80780</td>\n",
       "      <td>-73.93837</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>110</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48840</th>\n",
       "      <td>36452965</td>\n",
       "      <td>❥❥NYC Apt: 4min/subway, 25m/city, 20m/LGA,JFK❥❥</td>\n",
       "      <td>63272360</td>\n",
       "      <td>Annie Lawrence</td>\n",
       "      <td>Queens</td>\n",
       "      <td>Woodhaven</td>\n",
       "      <td>40.69389</td>\n",
       "      <td>-73.86823</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>140</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48860</th>\n",
       "      <td>36468386</td>\n",
       "      <td>纽约罗岛Roosevelt Island整租或合租 窗外美景 设施全 家具新 到曼哈顿方便 ...</td>\n",
       "      <td>228268650</td>\n",
       "      <td>Yan</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Roosevelt Island</td>\n",
       "      <td>40.76688</td>\n",
       "      <td>-73.94688</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>145</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48861</th>\n",
       "      <td>36468409</td>\n",
       "      <td>One bedroom Manhattan Upper East Side Apartment</td>\n",
       "      <td>57502664</td>\n",
       "      <td>Omar</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper East Side</td>\n",
       "      <td>40.76628</td>\n",
       "      <td>-73.95795</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48862</th>\n",
       "      <td>36468880</td>\n",
       "      <td>Private room in a nice Brooklyn apartment</td>\n",
       "      <td>274195458</td>\n",
       "      <td>Abayomi</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick</td>\n",
       "      <td>40.69308</td>\n",
       "      <td>-73.91025</td>\n",
       "      <td>Private room</td>\n",
       "      <td>130</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48875</th>\n",
       "      <td>36478343</td>\n",
       "      <td>Welcome all as family</td>\n",
       "      <td>274273284</td>\n",
       "      <td>Anastasia</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>40.78749</td>\n",
       "      <td>-73.94749</td>\n",
       "      <td>Private room</td>\n",
       "      <td>140</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48879</th>\n",
       "      <td>36480292</td>\n",
       "      <td>Gorgeous 1.5 Bdr with a private yard- Williams...</td>\n",
       "      <td>540335</td>\n",
       "      <td>Lee</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71728</td>\n",
       "      <td>-73.94394</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48880</th>\n",
       "      <td>36481315</td>\n",
       "      <td>The Raccoon Artist Studio in Williamsburg New ...</td>\n",
       "      <td>208514239</td>\n",
       "      <td>Melki</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Williamsburg</td>\n",
       "      <td>40.71232</td>\n",
       "      <td>-73.94220</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>120</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48888</th>\n",
       "      <td>36484087</td>\n",
       "      <td>Spacious Room w/ Private Rooftop, Central loca...</td>\n",
       "      <td>274321313</td>\n",
       "      <td>Kat</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Hell's Kitchen</td>\n",
       "      <td>40.76392</td>\n",
       "      <td>-73.99183</td>\n",
       "      <td>Private room</td>\n",
       "      <td>125</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48892</th>\n",
       "      <td>36485431</td>\n",
       "      <td>Sunny Studio at Historical Neighborhood</td>\n",
       "      <td>23492952</td>\n",
       "      <td>Ilgar &amp; Aysel</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Harlem</td>\n",
       "      <td>40.81475</td>\n",
       "      <td>-73.94867</td>\n",
       "      <td>Entire home/apt</td>\n",
       "      <td>115</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7982 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id                                               name    host_id  \\\n",
       "0          2539                 Clean & quiet apt home by the park       2787   \n",
       "10         5295                   Beautiful 1br on Upper West Side       7702   \n",
       "14         6090                      West Village Nest - Superhost      11975   \n",
       "15         6848                   Only 2 stops to Manhattan studio      15991   \n",
       "17         7322                                    Chelsea Perfect      18946   \n",
       "21         8024                     CBG CtyBGd HelpsHaiti rm#1:1-4      22486   \n",
       "23         8110                              CBG Helps Haiti Rm #2      22486   \n",
       "24         8490             MAISON DES SIRENES1,bohemian apartment      25183   \n",
       "41        12299                Beautiful Sunny Park Slope Brooklyn      47610   \n",
       "42        12303                  1bdr w private bath. in lofty apt      47618   \n",
       "43        12318                                  West Side Retreat      16800   \n",
       "46        12937  1 Stop fr. Manhattan! Private Suite,Landmark B...      50124   \n",
       "47        12940                 Charming Brownstone 3 - Near PRATT      50148   \n",
       "48        13050                          bright and stylish duplex      50846   \n",
       "53        14314                    Greenpoint Place...Has It All!       56246   \n",
       "56        14991                 Great Location, Manhattan Bedroom!      59023   \n",
       "74        17747                              BLUE TRIM GUEST HOUSE      68599   \n",
       "80        18764                         Cozy 2 BR in Williamsburg       72014   \n",
       "81        19159               Spacious luminous apt Upper West NYC      73051   \n",
       "83        19282                    Sunny, Spacious Top Floor Haven      73469   \n",
       "86        19812        2 bedroom Williamsburg Apt - Bedford L stop      74857   \n",
       "91        20734                Spacious Prospect Heights Apartment      78460   \n",
       "95        21293                     Sunny Apartment in Artist Home      44145   \n",
       "96        21456                 Light-filled classic Central Park       42032   \n",
       "99        22911                The Stuydio Modern and Light Filled      87773   \n",
       "104       24143  Williamsburg—Steps To Subway, Private Bath&Bal...      97219   \n",
       "106       25235                  Large 2 Bedroom Great for Groups!      87773   \n",
       "111       26520       Cozy Room #3, Landmark Home 1 Block to PRATT      51038   \n",
       "112       26559                   Beautiful Apartment East Village     112793   \n",
       "113       26785                       Park Slope Green Guest House      42273   \n",
       "...         ...                                                ...        ...   \n",
       "48702  36390301    3 Bedroom Apt in Ridgewood, 20 Min to Manhattan  273632292   \n",
       "48704  36391474                 Wonderful apartment close to Metro  273025497   \n",
       "48706  36391866  Clean, modern, and comfy  1bd apt Manhattan-Ha...  273644177   \n",
       "48710  36394726          1 bed available in a 2bd/1ba Bushwick Gem  239638986   \n",
       "48731  36410519    Sunlight charming apt. in the heart of Brooklyn  121384174   \n",
       "48736  36412880          Massive Master Bedroom w Private Bathroom    3427758   \n",
       "48737  36413114          Studio on West 14th Street and 7th Avenue  273772372   \n",
       "48756  36419441                            Murray Hill Masterpiece  273824202   \n",
       "48764  36421786    Luxury | Private room |Balcony|Parking included  211500809   \n",
       "48765  36421796                    Cozy Room with Private Bathroom  273843157   \n",
       "48767  36422573  Romantic studio in New York artistic best Bush...  273849259   \n",
       "48771  36423944                    Modern room in luxury apartment  271350187   \n",
       "48776  36424509        Brooklyn Loft : Comfort & Sunset City Views    8411075   \n",
       "48782  36425863         Lovely Privet Bedroom with Privet Restroom   83554966   \n",
       "48783  36426093                                   Best room in nyc  273877318   \n",
       "48795  36429652        Cute double room for the perfect Yankee fan   58222366   \n",
       "48798  36438110  Location! View!  X- Large Studio w/ Washer/Dryer!   96079975   \n",
       "48803  36441808                  Hell's Kitchen charming apartment   24680496   \n",
       "48806  36442487                       Endless Elegance in Brooklyn  199213364   \n",
       "48809  36444734  Sunny Upper West Side Apt. 3mins from Central ...   32987938   \n",
       "48818  36447795  Beautiful studio Apt. in Harlem (near Red Roos...  274035866   \n",
       "48840  36452965    ❥❥NYC Apt: 4min/subway, 25m/city, 20m/LGA,JFK❥❥   63272360   \n",
       "48860  36468386  纽约罗岛Roosevelt Island整租或合租 窗外美景 设施全 家具新 到曼哈顿方便 ...  228268650   \n",
       "48861  36468409    One bedroom Manhattan Upper East Side Apartment   57502664   \n",
       "48862  36468880          Private room in a nice Brooklyn apartment  274195458   \n",
       "48875  36478343                              Welcome all as family  274273284   \n",
       "48879  36480292  Gorgeous 1.5 Bdr with a private yard- Williams...     540335   \n",
       "48880  36481315  The Raccoon Artist Studio in Williamsburg New ...  208514239   \n",
       "48888  36484087  Spacious Room w/ Private Rooftop, Central loca...  274321313   \n",
       "48892  36485431            Sunny Studio at Historical Neighborhood   23492952   \n",
       "\n",
       "            host_name neighbourhood_group       neighbourhood  latitude  \\\n",
       "0                John            Brooklyn          Kensington  40.64749   \n",
       "10               Lena           Manhattan     Upper West Side  40.80316   \n",
       "14              Alina           Manhattan        West Village  40.73530   \n",
       "15      Allen & Irina            Brooklyn        Williamsburg  40.70837   \n",
       "17               Doti           Manhattan             Chelsea  40.74192   \n",
       "21              Lisel            Brooklyn          Park Slope  40.68069   \n",
       "23              Lisel            Brooklyn          Park Slope  40.68001   \n",
       "24           Nathalie            Brooklyn  Bedford-Stuyvesant  40.68371   \n",
       "41              Abdul            Brooklyn         South Slope  40.66278   \n",
       "42            Yolande            Brooklyn         Fort Greene  40.69673   \n",
       "43                Cyn           Manhattan     Upper West Side  40.79009   \n",
       "46            Orestes              Queens    Long Island City  40.74771   \n",
       "47           Adreinne            Brooklyn  Bedford-Stuyvesant  40.68111   \n",
       "48           Jennifer            Brooklyn  Bedford-Stuyvesant  40.68554   \n",
       "53             Jeanne            Brooklyn          Greenpoint  40.73506   \n",
       "56             Bianca           Manhattan     Lower East Side  40.72004   \n",
       "74             George            Brooklyn        Clinton Hill  40.68346   \n",
       "80               Lulú            Brooklyn        Williamsburg  40.71154   \n",
       "81            Sybilla           Manhattan              Harlem  40.82915   \n",
       "83               Gaia            Brooklyn            Flatbush  40.65401   \n",
       "86            Starlee            Brooklyn        Williamsburg  40.71833   \n",
       "91     Sean & Lynette            Brooklyn    Prospect Heights  40.68233   \n",
       "95             Tyrome            Brooklyn            Bushwick  40.70093   \n",
       "96               Dana           Manhattan     Upper West Side  40.79764   \n",
       "99             Shelly            Brooklyn  Bedford-Stuyvesant  40.68413   \n",
       "104              Seth            Brooklyn        Williamsburg  40.71332   \n",
       "106            Shelly            Brooklyn  Bedford-Stuyvesant  40.68373   \n",
       "111             Erica            Brooklyn        Clinton Hill  40.68698   \n",
       "112             Sally           Manhattan        East Village  40.72880   \n",
       "113              Dani            Brooklyn         South Slope  40.66853   \n",
       "...               ...                 ...                 ...       ...   \n",
       "48702            Pete              Queens           Ridgewood  40.70268   \n",
       "48704         Richard            Brooklyn         Fort Greene  40.68868   \n",
       "48706           Merce           Manhattan              Harlem  40.80078   \n",
       "48710           Marné            Brooklyn            Bushwick  40.69287   \n",
       "48731   Luciana Paula            Brooklyn          Park Slope  40.66716   \n",
       "48736            Phil           Manhattan              Harlem  40.81274   \n",
       "48737         Richard           Manhattan        West Village  40.73713   \n",
       "48756           David           Manhattan         Murray Hill  40.74404   \n",
       "48764        Stefania              Queens     Jackson Heights  40.74765   \n",
       "48765         Matheus            Brooklyn          Greenpoint  40.73164   \n",
       "48767       Alexander            Brooklyn            Bushwick  40.69958   \n",
       "48771           Elena            Brooklyn          Greenpoint  40.71918   \n",
       "48776          Ramiro            Brooklyn            Bushwick  40.69608   \n",
       "48782           Rusaa           Manhattan     Upper East Side  40.78099   \n",
       "48783             Jay               Bronx   Claremont Village  40.83926   \n",
       "48795       Dominique               Bronx   Claremont Village  40.83502   \n",
       "48798           Karen           Manhattan     Upper East Side  40.78411   \n",
       "48803          Miriam           Manhattan      Hell's Kitchen  40.76911   \n",
       "48806           Eeman            Brooklyn      Sheepshead Bay  40.59731   \n",
       "48809            Alex           Manhattan     Upper West Side  40.77889   \n",
       "48818        Aurellia           Manhattan         East Harlem  40.80780   \n",
       "48840  Annie Lawrence              Queens           Woodhaven  40.69389   \n",
       "48860             Yan           Manhattan    Roosevelt Island  40.76688   \n",
       "48861            Omar           Manhattan     Upper East Side  40.76628   \n",
       "48862         Abayomi            Brooklyn            Bushwick  40.69308   \n",
       "48875       Anastasia           Manhattan         East Harlem  40.78749   \n",
       "48879             Lee            Brooklyn        Williamsburg  40.71728   \n",
       "48880           Melki            Brooklyn        Williamsburg  40.71232   \n",
       "48888             Kat           Manhattan      Hell's Kitchen  40.76392   \n",
       "48892   Ilgar & Aysel           Manhattan              Harlem  40.81475   \n",
       "\n",
       "       longitude        room_type  price  minimum_nights  number_of_reviews  \\\n",
       "0      -73.97237     Private room    149               1                  9   \n",
       "10     -73.96545  Entire home/apt    135               5                 53   \n",
       "14     -74.00525  Entire home/apt    120              90                 27   \n",
       "15     -73.95352  Entire home/apt    140               2                148   \n",
       "17     -73.99501     Private room    140               1                260   \n",
       "21     -73.97706     Private room    130               2                130   \n",
       "23     -73.97865     Private room    110               2                 71   \n",
       "24     -73.94028  Entire home/apt    120               2                 88   \n",
       "41     -73.97966  Entire home/apt    120               3                 15   \n",
       "42     -73.97584     Private room    120               7                 25   \n",
       "43     -73.97927     Private room    135               4                 81   \n",
       "46     -73.94740     Private room    130               3                248   \n",
       "47     -73.95591  Entire home/apt    110               7                 61   \n",
       "48     -73.94090  Entire home/apt    115               3                 11   \n",
       "53     -73.95392  Entire home/apt    144               2                328   \n",
       "56     -73.99104     Private room    110               5                 19   \n",
       "74     -73.96374     Private room    105               2                105   \n",
       "80     -73.96112     Private room    145               3                 61   \n",
       "81     -73.95136  Entire home/apt    110              31                 54   \n",
       "83     -73.96323  Entire home/apt    130               6                 16   \n",
       "86     -73.95748  Entire home/apt    105               3                 61   \n",
       "91     -73.97261  Entire home/apt    131               4                166   \n",
       "95     -73.92609  Entire home/apt    105               3                118   \n",
       "96     -73.96177  Entire home/apt    140               3                 81   \n",
       "99     -73.92357  Entire home/apt    125               7                139   \n",
       "104    -73.94177     Private room    101               3                335   \n",
       "106    -73.92377  Entire home/apt    125              90                162   \n",
       "111    -73.96572     Private room    125               2                 19   \n",
       "112    -73.98192  Entire home/apt    140               7                 12   \n",
       "113    -73.98912  Entire home/apt    120              30                467   \n",
       "...          ...              ...    ...             ...                ...   \n",
       "48702  -73.90353  Entire home/apt    110              24                  0   \n",
       "48704  -73.97671  Entire home/apt    107               1                  0   \n",
       "48706  -73.95079  Entire home/apt    137               1                  0   \n",
       "48710  -73.92289     Private room    125               1                  0   \n",
       "48731  -73.98101  Entire home/apt    111               8                  0   \n",
       "48736  -73.94357     Private room    110               3                  0   \n",
       "48737  -73.99870  Entire home/apt    144               1                  0   \n",
       "48756  -73.97239  Entire home/apt    129               2                  0   \n",
       "48764  -73.89445     Private room    110               2                  0   \n",
       "48765  -73.95187     Private room    105               1                  0   \n",
       "48767  -73.92772  Entire home/apt    120               1                  0   \n",
       "48771  -73.94853     Private room    130               1                  0   \n",
       "48776  -73.91210  Entire home/apt    119               2                  0   \n",
       "48782  -73.95366     Private room    129               1                  1   \n",
       "48783  -73.91173     Private room    140               1                  0   \n",
       "48795  -73.91058     Private room    125               2                  0   \n",
       "48798  -73.94870  Entire home/apt    140               7                  0   \n",
       "48803  -73.99248  Entire home/apt    145               1                  0   \n",
       "48806  -73.93381  Entire home/apt    140               7                  0   \n",
       "48809  -73.97668  Entire home/apt    143               3                  0   \n",
       "48818  -73.93837  Entire home/apt    110               2                  0   \n",
       "48840  -73.86823  Entire home/apt    140               3                  0   \n",
       "48860  -73.94688  Entire home/apt    145               1                  0   \n",
       "48861  -73.95795  Entire home/apt    120               1                  0   \n",
       "48862  -73.91025     Private room    130               1                  0   \n",
       "48875  -73.94749     Private room    140               1                  0   \n",
       "48879  -73.94394  Entire home/apt    120              20                  0   \n",
       "48880  -73.94220  Entire home/apt    120               1                  0   \n",
       "48888  -73.99183     Private room    125               4                  0   \n",
       "48892  -73.94867  Entire home/apt    115              10                  0   \n",
       "\n",
       "      last_review  reviews_per_month  calculated_host_listings_count  \\\n",
       "0      2018-10-19               0.21                               6   \n",
       "10     2019-06-22               0.43                               1   \n",
       "14     2018-10-31               0.22                               1   \n",
       "15     2019-06-29               1.20                               1   \n",
       "17     2019-07-01               2.12                               1   \n",
       "21     2019-07-01               1.09                               6   \n",
       "23     2019-07-02               0.61                               6   \n",
       "24     2019-06-19               0.73                               2   \n",
       "41     2019-05-27               0.39                               1   \n",
       "42     2018-09-30               0.23                               1   \n",
       "43     2019-06-16               0.69                               1   \n",
       "46     2019-07-01               2.25                               1   \n",
       "47     2019-05-25               0.52                               1   \n",
       "48     2017-01-01               0.10                               1   \n",
       "53     2019-06-29               2.82                               1   \n",
       "56     2019-05-18               0.17                               1   \n",
       "74     2019-06-26               0.92                               1   \n",
       "80     2019-04-22               0.54                               4   \n",
       "81     2019-03-23               0.49                               1   \n",
       "83     2019-06-15               0.15                               1   \n",
       "86     2018-08-09               0.53                               1   \n",
       "91     2019-06-27               3.40                               1   \n",
       "95     2019-06-18               1.05                               2   \n",
       "96     2019-07-07               0.71                               1   \n",
       "99     2018-10-28               1.23                               2   \n",
       "104    2019-05-29               3.02                               1   \n",
       "106    2019-06-28               1.46                               2   \n",
       "111    2019-06-02               0.20                               6   \n",
       "112    2017-12-11               0.13                               1   \n",
       "113    2018-12-30               4.22                               2   \n",
       "...           ...                ...                             ...   \n",
       "48702         NaN                NaN                               1   \n",
       "48704         NaN                NaN                               1   \n",
       "48706         NaN                NaN                               1   \n",
       "48710         NaN                NaN                               1   \n",
       "48731         NaN                NaN                               1   \n",
       "48736         NaN                NaN                               1   \n",
       "48737         NaN                NaN                               1   \n",
       "48756         NaN                NaN                               1   \n",
       "48764         NaN                NaN                               1   \n",
       "48765         NaN                NaN                               1   \n",
       "48767         NaN                NaN                               1   \n",
       "48771         NaN                NaN                               3   \n",
       "48776         NaN                NaN                               1   \n",
       "48782  2019-07-07               1.00                               1   \n",
       "48783         NaN                NaN                               1   \n",
       "48795         NaN                NaN                               1   \n",
       "48798         NaN                NaN                               1   \n",
       "48803         NaN                NaN                               1   \n",
       "48806         NaN                NaN                               2   \n",
       "48809         NaN                NaN                               1   \n",
       "48818         NaN                NaN                               1   \n",
       "48840         NaN                NaN                               6   \n",
       "48860         NaN                NaN                               1   \n",
       "48861         NaN                NaN                               1   \n",
       "48862         NaN                NaN                               1   \n",
       "48875         NaN                NaN                               1   \n",
       "48879         NaN                NaN                               1   \n",
       "48880         NaN                NaN                               3   \n",
       "48888         NaN                NaN                               1   \n",
       "48892         NaN                NaN                               1   \n",
       "\n",
       "       availability_365  \n",
       "0                   365  \n",
       "10                    6  \n",
       "14                    0  \n",
       "15                   46  \n",
       "17                   12  \n",
       "21                  347  \n",
       "23                  304  \n",
       "24                  233  \n",
       "41                  345  \n",
       "42                  311  \n",
       "43                  273  \n",
       "46                  215  \n",
       "47                  265  \n",
       "48                    0  \n",
       "53                  234  \n",
       "56                  301  \n",
       "74                  304  \n",
       "80                  238  \n",
       "81                  209  \n",
       "83                   38  \n",
       "86                  272  \n",
       "91                  207  \n",
       "95                    9  \n",
       "96                  198  \n",
       "99                  311  \n",
       "104                 152  \n",
       "106                 137  \n",
       "111                 250  \n",
       "112                 164  \n",
       "113                 192  \n",
       "...                 ...  \n",
       "48702               183  \n",
       "48704                49  \n",
       "48706                35  \n",
       "48710               175  \n",
       "48731                 0  \n",
       "48736               199  \n",
       "48737               110  \n",
       "48756                 0  \n",
       "48764                85  \n",
       "48765               199  \n",
       "48767               363  \n",
       "48771               360  \n",
       "48776                 5  \n",
       "48782               147  \n",
       "48783                90  \n",
       "48795               364  \n",
       "48798               158  \n",
       "48803                10  \n",
       "48806               171  \n",
       "48809                10  \n",
       "48818                25  \n",
       "48840               232  \n",
       "48860                30  \n",
       "48861                 1  \n",
       "48862                83  \n",
       "48875               180  \n",
       "48879                22  \n",
       "48880               365  \n",
       "48888                31  \n",
       "48892                27  \n",
       "\n",
       "[7982 rows x 16 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.query(\"price > 100 and price < 150\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Activity 3 (bonus): modeling AirBnb prices"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "<img src=\"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Antu_task-complete.svg/1024px-Antu_task-complete.svg.png\" width=50 align=left/>\n",
    "\n",
    "Our question is the following: \"is the price of a listing increasing with the number of reviews it received?\"\n",
    "\n",
    "* Plot the price of all listings as a function of the number of reviews they received. Make a few observations on the plot.\n",
    "* Fit a linear model to describe the evolution of listing price as a function of the number of reviews. Does the model properly describe the data? How would you improve it?\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "prices = df[\"price\"]\n",
    "reviews = df[\"number_of_reviews\"]\n",
    "p = polyfit(reviews, prices, 1)\n",
    "plt.plot(reviews, prices, '+')\n",
    "plt.plot(sorted(reviews), polyval(p, sorted(reviews)))\n",
    "plt.ylim(0, 2000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}